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7,539,939 | 7 | 10 | 7. The method according to claim 1 , further comprising: concurrently displaying the same text in the font preview display area in a third font format, wherein the text displayed in the third font format includes the same plural characters in the first order, and wherein the third font format differs from the first and second font formats. | 7. The method according to claim 1 , further comprising: concurrently displaying the same text in the font preview display area in a third font format, wherein the text displayed in the third font format includes the same plural characters in the first order, and wherein the third font format differs from the first and second font formats. 10. The method according to claim 7 , wherein the first font format, the second font format, and the third font format are part of a predefined font group. | 0.5 |
8,577,908 | 6 | 13 | 6. A computer-implemented method of preventing alterations of physical entities of data in a database when a query is executed against the database, comprising: providing a logical representation of the data defining a multiplicity of logical fields, each logical field abstractly describing a manner of accessing and exposing, via a user interface, an associated physical entity of the data; wherein each of the multiplicity of logical fields include a reference to an access method selected from at least two different access method types; wherein the at least two different access method types are selected from the group comprising: (i) a simple access method which maps a respective one of the plurality of logical fields directly to a physical entity, (ii) a filtered access method which identifies a physical entity and provides rules used to define a subset of items within the physical entities, and (iii) a composed access method which computes a value for a respective one of the plurality of logical fields from one or more physical entities using an expression supplied as part of a composed access method definition; wherein each of the different access methods types defines a different manner of exposing the respective physical entity of the data; and wherein at least a portion of the multiplicity of logical fields include lock attributes referenced in order to lock the respective logical field; providing a lock object for each logical field of a plurality of logical fields forming a subset of the multiplicity of logical fields, the respective lock object being identified by the respective lock attributes of the respective logical field; receiving an abstract query from a requesting entity comprising at least one logical field of the multiplicity of logical fields; and upon determining that executing the abstract query against the database requires the lock on the at least one logical field; determining the lock object of the at least one logical field; locking the lock object for the requesting entity for locking the at least one logical field before executing the abstract query; and unlocking the lock object for the requesting entity after executing the abstract query. | 6. A computer-implemented method of preventing alterations of physical entities of data in a database when a query is executed against the database, comprising: providing a logical representation of the data defining a multiplicity of logical fields, each logical field abstractly describing a manner of accessing and exposing, via a user interface, an associated physical entity of the data; wherein each of the multiplicity of logical fields include a reference to an access method selected from at least two different access method types; wherein the at least two different access method types are selected from the group comprising: (i) a simple access method which maps a respective one of the plurality of logical fields directly to a physical entity, (ii) a filtered access method which identifies a physical entity and provides rules used to define a subset of items within the physical entities, and (iii) a composed access method which computes a value for a respective one of the plurality of logical fields from one or more physical entities using an expression supplied as part of a composed access method definition; wherein each of the different access methods types defines a different manner of exposing the respective physical entity of the data; and wherein at least a portion of the multiplicity of logical fields include lock attributes referenced in order to lock the respective logical field; providing a lock object for each logical field of a plurality of logical fields forming a subset of the multiplicity of logical fields, the respective lock object being identified by the respective lock attributes of the respective logical field; receiving an abstract query from a requesting entity comprising at least one logical field of the multiplicity of logical fields; and upon determining that executing the abstract query against the database requires the lock on the at least one logical field; determining the lock object of the at least one logical field; locking the lock object for the requesting entity for locking the at least one logical field before executing the abstract query; and unlocking the lock object for the requesting entity after executing the abstract query. 13. The method of claim 6 , wherein the lock attributes of the at least one logical field comprises a synchronization indication of whether a lock on the logical field is required or not and a lock item indication of whether a lock on a corresponding physical entity of the data is required or not, and wherein locking the lock object for the requesting entity comprises: upon determining, from the synchronization indication, that executing the abstract query against the database requires a lock on the at least one logical field, locking the lock object; and upon determining, from the lock item indication, whether executing the abstract query against the database requires a lock on the corresponding physical entity of the data, locking the corresponding physical entity before executing the abstract query. | 0.5 |
10,044,750 | 1 | 7 | 1. A computer-implemented method comprising: receiving a plurality of script code samples; transforming the plurality of script code samples into a plurality of tokenized samples, the transforming based on syntactical elements of the plurality of script code samples; identifying one or more similarities between at least a first tokenized sample of the plurality of tokenized samples and a second tokenized sample of the plurality of tokenized samples; based at least in part on the one or more similarities, identifying a cluster of samples including at least the first tokenized sample and the second tokenized sample; selecting the first tokenized sample as a representative sample of the cluster of samples; identifying known malicious code having a threshold similarity to the representative sample by de-obfuscating the representative sample of the cluster of samples to produce a de-obfuscated representative sample and comparing the de-obfuscated representative sample to a plurality of known malicious code samples; based on the identified known malicious code, labeling each of the samples in the cluster of samples as malicious, wherein the label of each of the samples in the cluster of samples as malicious is unscored; and generating, based at least on the unscored labeled samples in the cluster of samples, a generalized code signature, wherein the generalized code signature identifies the first tokenized sample and the second tokenized sample. | 1. A computer-implemented method comprising: receiving a plurality of script code samples; transforming the plurality of script code samples into a plurality of tokenized samples, the transforming based on syntactical elements of the plurality of script code samples; identifying one or more similarities between at least a first tokenized sample of the plurality of tokenized samples and a second tokenized sample of the plurality of tokenized samples; based at least in part on the one or more similarities, identifying a cluster of samples including at least the first tokenized sample and the second tokenized sample; selecting the first tokenized sample as a representative sample of the cluster of samples; identifying known malicious code having a threshold similarity to the representative sample by de-obfuscating the representative sample of the cluster of samples to produce a de-obfuscated representative sample and comparing the de-obfuscated representative sample to a plurality of known malicious code samples; based on the identified known malicious code, labeling each of the samples in the cluster of samples as malicious, wherein the label of each of the samples in the cluster of samples as malicious is unscored; and generating, based at least on the unscored labeled samples in the cluster of samples, a generalized code signature, wherein the generalized code signature identifies the first tokenized sample and the second tokenized sample. 7. The computer-implemented method of claim 1 , wherein the generating the generalized code signature includes: identifying a common subsequence of tokens shared by ones of the plurality of tokenized samples that correspond to each of the code samples in the cluster of samples that is labeled malicious; generating an expression usable to match code portions from respective ones of the code samples in the cluster of samples, the code portions corresponding to the common subsequence of tokens; and including the expression in the generalized code signature. | 0.5 |
8,990,769 | 11 | 13 | 11. An article comprising: a non-transitory storage medium comprising instructions stored thereon to, said instructions being executable by a computing device to: transform between at least first and at least second non-transitory stored binary digital signal quantities respectively representing at least a first and at least a second expression, said represented expressions to have a common view for non-common expression types of said represented expressions and to have a non-common view for common expression types of said represented expressions, said represented expressions to comprise at least one of the following expression types: a hierarchical edge and/or node labeled tree or a symbol string. | 11. An article comprising: a non-transitory storage medium comprising instructions stored thereon to, said instructions being executable by a computing device to: transform between at least first and at least second non-transitory stored binary digital signal quantities respectively representing at least a first and at least a second expression, said represented expressions to have a common view for non-common expression types of said represented expressions and to have a non-common view for common expression types of said represented expressions, said represented expressions to comprise at least one of the following expression types: a hierarchical edge and/or node labeled tree or a symbol string. 13. The article of claim 11 , wherein said first represented expression to comprise a hierarchical edge and/or node labeled tree and said second represented expression to comprise a symbol string. | 0.621622 |
8,060,231 | 1 | 12 | 1. One or more computer storage media including computer executable instructions embodied thereon that, when executed by one or more computing devices, cause the one or more computing devices to perform a method for generating instructions for filling a predetermined region, the method comprising: receiving a dithered specification for the predetermined region; generating a lattice corresponding to the dithered specification, wherein the lattice is populated with a set of vertices, a set of edges connecting the vertices, and cost function data associated with the edges on-the-fly; recursively performing an overlapping divide-and-conquer beam search on the lattice to determine a path through a subset of vertices included in the lattice that minimizes an overall cost of filling the predetermined region, wherein the overall cost is calculated from the cost function data associated with the edges that connect the subset of vertices; and outputting instructions to a processor for the placement of building blocks in the predetermined region, the instructions generated using the determined path. | 1. One or more computer storage media including computer executable instructions embodied thereon that, when executed by one or more computing devices, cause the one or more computing devices to perform a method for generating instructions for filling a predetermined region, the method comprising: receiving a dithered specification for the predetermined region; generating a lattice corresponding to the dithered specification, wherein the lattice is populated with a set of vertices, a set of edges connecting the vertices, and cost function data associated with the edges on-the-fly; recursively performing an overlapping divide-and-conquer beam search on the lattice to determine a path through a subset of vertices included in the lattice that minimizes an overall cost of filling the predetermined region, wherein the overall cost is calculated from the cost function data associated with the edges that connect the subset of vertices; and outputting instructions to a processor for the placement of building blocks in the predetermined region, the instructions generated using the determined path. 12. The one or more computer storage media of claim 1 , wherein the method further comprises presenting the instructions as a visual representation of building block placement. | 0.541667 |
9,324,024 | 11 | 16 | 11. A method to generate a pseudo message recognizable as such by an intended recipient, the method comprising: generating an error sentence that is inconsistent with a rule in a recipient Ontology associated with a recipient; selecting a piece of text as background content; and inserting the error sentence into the background content to form the pseudo message. | 11. A method to generate a pseudo message recognizable as such by an intended recipient, the method comprising: generating an error sentence that is inconsistent with a rule in a recipient Ontology associated with a recipient; selecting a piece of text as background content; and inserting the error sentence into the background content to form the pseudo message. 16. The method of claim 11 , wherein generating an error sentence that is inconsistent with a rule in the recipient Ontology comprises: selecting the rule from among a plurality of rules of the recipient Ontology; expressing the rule as a correct sentence; and replacing a word in the correct sentence, the word representing a concept of the rule, with an irrelevant word from an available lexicon to form the error sentence. | 0.5 |
10,090,002 | 13 | 16 | 13. The computer program product of claim 12 , wherein, for each user in the set of users, the at least one attribute comprises at least one personality trait of the user. | 13. The computer program product of claim 12 , wherein, for each user in the set of users, the at least one attribute comprises at least one personality trait of the user. 16. The computer program product of claim 13 , wherein the computer readable program further causes the computing device to generate the aggregate user model at least by at least one of combining a like personality trait, of the set of users, that are within a standard deviation of a variance of the like personality trait, or combining personality traits, of the set of users, that are within a fixed range for a majority of the users in the set of users. | 0.661481 |
9,038,037 | 5 | 6 | 5. A method of claim 1 where an element of a context qualified type definition may be a precursor element that stands in for some concrete entity whose value is not yet know when said context qualified type is initially defined. | 5. A method of claim 1 where an element of a context qualified type definition may be a precursor element that stands in for some concrete entity whose value is not yet know when said context qualified type is initially defined. 6. A method of claim 5 where said precursor element may be a variable parameter. | 0.5 |
8,005,879 | 1 | 8 | 1. A method comprising: determining a service executing on an originating device of a network of devices in which a plurality of services are deployed and configured to process information external to the network of devices and collected by at least one sensor associated with the network of devices, the service including executable code; determining a cause for re-deployment of the service executing on the originating device; mapping the service to a selected device from among the network of devices that includes the originating device and the selected device; and re-deploying the service on the selected device including transferring the executable code to the selected device for execution thereon and for continued processing of the external information therewith, wherein determining a cause for re-deployment of the service comprises: determining that the selected device is available for re-deployment of the service; and determining device metadata associated with the originating device and/or the selected device that indicates that the selected device is better able to execute the service, including determining the device metadata by representing device characteristics of the originating device and the selected device in a common format; value-matching the device characteristics of each of the originating device and the selected device to service characteristics of the service as represented in associated service metadata, and selecting the selected device as having a closer value-match of device characteristics to the service characteristics than the originating device. | 1. A method comprising: determining a service executing on an originating device of a network of devices in which a plurality of services are deployed and configured to process information external to the network of devices and collected by at least one sensor associated with the network of devices, the service including executable code; determining a cause for re-deployment of the service executing on the originating device; mapping the service to a selected device from among the network of devices that includes the originating device and the selected device; and re-deploying the service on the selected device including transferring the executable code to the selected device for execution thereon and for continued processing of the external information therewith, wherein determining a cause for re-deployment of the service comprises: determining that the selected device is available for re-deployment of the service; and determining device metadata associated with the originating device and/or the selected device that indicates that the selected device is better able to execute the service, including determining the device metadata by representing device characteristics of the originating device and the selected device in a common format; value-matching the device characteristics of each of the originating device and the selected device to service characteristics of the service as represented in associated service metadata, and selecting the selected device as having a closer value-match of device characteristics to the service characteristics than the originating device. 8. The method of claim 1 wherein mapping the service to a selected device comprises: imposing a time limit to be met before the service may be re-deployed from the selected device back to the originating device, or to another device of the plurality of devices. | 0.633427 |
9,081,782 | 11 | 12 | 11. A computer program product for implementing within a computer system a method for dynamically generating a graphical memorabilia project, the computer program product comprising: a computer-readable, non-transitory medium for providing computer program code means utilized to implement the method, wherein the computer program code means is comprised of executable code for implementing: providing a dynamic page layout template having a first well of a first well type and multiple wells of a second well type, wherein a location of the first well of the first well type and locations of the wells of the second well type are fixed with respect to the template, wherein the first well will accept an image while preventing one or more background design elements from being disposed therein, wherein each of the one or more background design elements comprises a virtual design that is configured to resemble a decorative element for use in a physical memorabilia project, wherein each of the wells of the second well type will accept an individual background design element, while preventing the image from being disposed therein, wherein the wells of the second well type are divided into well classes, and wherein wells of the second well type that are of the same well class are governed by similar pre-determined rules, such that a change to one of the wells that is of the second well type and of a first well class will cause a similar change to another well of the second well type and of the first well class; and placing the image in the first well. | 11. A computer program product for implementing within a computer system a method for dynamically generating a graphical memorabilia project, the computer program product comprising: a computer-readable, non-transitory medium for providing computer program code means utilized to implement the method, wherein the computer program code means is comprised of executable code for implementing: providing a dynamic page layout template having a first well of a first well type and multiple wells of a second well type, wherein a location of the first well of the first well type and locations of the wells of the second well type are fixed with respect to the template, wherein the first well will accept an image while preventing one or more background design elements from being disposed therein, wherein each of the one or more background design elements comprises a virtual design that is configured to resemble a decorative element for use in a physical memorabilia project, wherein each of the wells of the second well type will accept an individual background design element, while preventing the image from being disposed therein, wherein the wells of the second well type are divided into well classes, and wherein wells of the second well type that are of the same well class are governed by similar pre-determined rules, such that a change to one of the wells that is of the second well type and of a first well class will cause a similar change to another well of the second well type and of the first well class; and placing the image in the first well. 12. The computer program product of claim 11 , wherein the computer program code means is further comprised of executable code for implementing a step for making a change to one of the wells of the second well type and of a second class, wherein the change to the one of the wells of the second well type and of the second class automatically cause a similar change to another well of the second well type and of the second well class. | 0.622396 |
8,719,353 | 1 | 2 | 1. A computerized method for creating a multimedia file from user input data, the method comprising: receiving user input data representative of text and voice data in a user input receiver; storing said user input data and other data which includes visualization data and advertising inserts in a persistent storage device; processing said user input data in order to associate said user input data with one or more visualizations by way of a computer under program control representative of the meaning of said user input data; and generating a multimedia file from said one or more visualizations and at least one of said advertising inserts by way of a computer under program control that conveys the meaning of said user input data, wherein said generating step includes the step of automatically selecting one or both of said advertising insert and said one or more visualizations. | 1. A computerized method for creating a multimedia file from user input data, the method comprising: receiving user input data representative of text and voice data in a user input receiver; storing said user input data and other data which includes visualization data and advertising inserts in a persistent storage device; processing said user input data in order to associate said user input data with one or more visualizations by way of a computer under program control representative of the meaning of said user input data; and generating a multimedia file from said one or more visualizations and at least one of said advertising inserts by way of a computer under program control that conveys the meaning of said user input data, wherein said generating step includes the step of automatically selecting one or both of said advertising insert and said one or more visualizations. 2. The computerized method as recited in claim 1 , wherein said generating step comprises: generating a multimedia file in which said one or more visualizations are presented in the same order as said user input data is received. | 0.5 |
9,396,192 | 14 | 15 | 14. The system of claim 11 , wherein the control circuitry is further configured to: retrieve closed-captioning information corresponding to the range of play positions; identify a subject based on the retrieved closed-captioning information; and associate the attribute with the identified subject. | 14. The system of claim 11 , wherein the control circuitry is further configured to: retrieve closed-captioning information corresponding to the range of play positions; identify a subject based on the retrieved closed-captioning information; and associate the attribute with the identified subject. 15. The system of claim 14 , wherein the subject is an actor, character or person within the media asset. | 0.789157 |
8,898,568 | 1 | 6 | 1. A method performed by a media player for providing an audio user interface to a user of the media player, the method comprising: receiving input indicative of an interaction of the user with a user interface associated with the media player; determining that an audio prompt is to be outputted; determining whether a communication channel to a voice prompt server remote from the media player is available to the media player; if the communication channel to the voice prompt server is available, receiving a prepared audio prompt from the voice prompt server; if the communication channel to the voice prompt server is not available, synthesizing a new audio prompt; and outputting at least a portion of one of the prepared audio prompt or the new audio prompt at the media player. | 1. A method performed by a media player for providing an audio user interface to a user of the media player, the method comprising: receiving input indicative of an interaction of the user with a user interface associated with the media player; determining that an audio prompt is to be outputted; determining whether a communication channel to a voice prompt server remote from the media player is available to the media player; if the communication channel to the voice prompt server is available, receiving a prepared audio prompt from the voice prompt server; if the communication channel to the voice prompt server is not available, synthesizing a new audio prompt; and outputting at least a portion of one of the prepared audio prompt or the new audio prompt at the media player. 6. The method of claim 1 further comprising: pausing playback of a media file in response to the output of the portion of the prepared audio prompt or the new audio prompt. | 0.855219 |
8,494,836 | 4 | 6 | 4. A computer program product for machine translation of web pages, the computer program product comprising: a non-transitory machine-readable storage medium having program instructions stored thereon, the program instruction to, retrieve a plurality of web pages of a website in response to an input of an address to the website; select a subset of the plurality of web pages based, at least in part, on positions of each of the plurality of web pages within a hierarchy of the website; machine translate the subset of the plurality of web pages from a first language to a second language to generate translations of the subset of web pages; receive a verification result from verification of the translations of the subset of web pages, wherein the verification result includes corrected translations of phrases in the subset of web pages; update a translation dictionary for machine translations, wherein said updating the translation dictionary corrects mistranslated phrases in the translations of the subset of web pages with the corrected translations of the phrases; and machine translate the plurality of web pages from the first language to the second language using the updated translation dictionary. | 4. A computer program product for machine translation of web pages, the computer program product comprising: a non-transitory machine-readable storage medium having program instructions stored thereon, the program instruction to, retrieve a plurality of web pages of a website in response to an input of an address to the website; select a subset of the plurality of web pages based, at least in part, on positions of each of the plurality of web pages within a hierarchy of the website; machine translate the subset of the plurality of web pages from a first language to a second language to generate translations of the subset of web pages; receive a verification result from verification of the translations of the subset of web pages, wherein the verification result includes corrected translations of phrases in the subset of web pages; update a translation dictionary for machine translations, wherein said updating the translation dictionary corrects mistranslated phrases in the translations of the subset of web pages with the corrected translations of the phrases; and machine translate the plurality of web pages from the first language to the second language using the updated translation dictionary. 6. The computer program product of claim 4 , wherein the program instructions to select the subset of the plurality of web pages based, at least in part, on positions of each of the plurality of web pages within the hierarchy of the website comprises program instructions to select from the plurality of web pages based on the respective positions until a predefined number of web pages have been selected. | 0.630909 |
8,521,821 | 1 | 10 | 1. At a web browser in a computing system, a method of sending a secure email via an email server, the method comprising: receiving user input requesting a compose email page user interface for a web-based email system; requesting the compose email page user interface from a server for the web-based mail system; receiving web page code from the server for the compose email page user interface; parsing the web page code for the compose email page user interface to determine screen locations of one or more user input interface elements including at least an email text box user input interface element; rendering the compose email page user interface in the browser, the compose email page user interface configured to receive plain text user input from a user; overlaying one or more browser-based user interface elements implemented integral to the browser and separate from the web page code from the server onto the compose email page user interface, wherein one or more of the browser-based interface elements are displayed at one or more of the determined screen locations, including overlaying a browser-based text box user input interface element over the email text box user input interface element; receiving unencrypted plain text user input in the overlaid browser-based text box user input interface element, wherein the unencrypted plain text user input is not available to the email server ; encrypting the unencrypted plain text user input received in the overlaid browser-based text box user input interface element to encrypted text, wherein encrypting the plain text user input comprises: sending a request to a key server for a sender key, wherein the request includes an identification of an entity sending the secure email; receiving a sender key, the sender key being derived from a master secret key and the identification of the entity sending the secure email; generating a sender-recipient key using the sender key and an identification of a recipient of the secure email; deriving an encryption key using the sender-recipient key; and using the encryption key, encrypting the user input received in the overlaid browser-based text box user input interface element; transferring the encrypted text from the overlaid browser-based text box user input interface element into the email text box user input interface element overlaid by the browser-based text box user input interface element; sending the secure email comprising the transferred encrypted text to an intended recipient via an email server; and wherein the email server is unable to decrypt the encrypted text. | 1. At a web browser in a computing system, a method of sending a secure email via an email server, the method comprising: receiving user input requesting a compose email page user interface for a web-based email system; requesting the compose email page user interface from a server for the web-based mail system; receiving web page code from the server for the compose email page user interface; parsing the web page code for the compose email page user interface to determine screen locations of one or more user input interface elements including at least an email text box user input interface element; rendering the compose email page user interface in the browser, the compose email page user interface configured to receive plain text user input from a user; overlaying one or more browser-based user interface elements implemented integral to the browser and separate from the web page code from the server onto the compose email page user interface, wherein one or more of the browser-based interface elements are displayed at one or more of the determined screen locations, including overlaying a browser-based text box user input interface element over the email text box user input interface element; receiving unencrypted plain text user input in the overlaid browser-based text box user input interface element, wherein the unencrypted plain text user input is not available to the email server ; encrypting the unencrypted plain text user input received in the overlaid browser-based text box user input interface element to encrypted text, wherein encrypting the plain text user input comprises: sending a request to a key server for a sender key, wherein the request includes an identification of an entity sending the secure email; receiving a sender key, the sender key being derived from a master secret key and the identification of the entity sending the secure email; generating a sender-recipient key using the sender key and an identification of a recipient of the secure email; deriving an encryption key using the sender-recipient key; and using the encryption key, encrypting the user input received in the overlaid browser-based text box user input interface element; transferring the encrypted text from the overlaid browser-based text box user input interface element into the email text box user input interface element overlaid by the browser-based text box user input interface element; sending the secure email comprising the transferred encrypted text to an intended recipient via an email server; and wherein the email server is unable to decrypt the encrypted text. 10. The method of claim 1 , wherein overlaying one or more browser-based user interface elements implemented integral to the browser and separate from the web page code from the server onto the compose email page user interface, wherein one or more of the browser-based interface elements are displayed at one or more of the determined screen locations is performed as a default behavior. | 0.674497 |
8,478,597 | 23 | 24 | 23. The non-transitory medium of claim 21 , wherein calculating the language model score comprises calculating a language model for the language of the non-native speaker and the second language. | 23. The non-transitory medium of claim 21 , wherein calculating the language model score comprises calculating a language model for the language of the non-native speaker and the second language. 24. The non-transitory medium of claim 23 , wherein calculating a language model for the language of the non-native speaker and the second language comprises phonetically transcribing the first language of the non-native speaker and the second language. | 0.5 |
9,269,358 | 1 | 6 | 1. A non-transitory computer-readable medium storing instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: obtaining, at a client device, a credential identifier for a credential that is associated with a user; periodically, at a predetermined time period: obtaining, at the client device, a time derived from a timing device of the client device; determining, at the client device, at least one index value using the credential identifier and the time derived from the timing device of the client device; accessing, at the client device, a predetermined set of associations between index values and words; generating, at the client device, a phrase corresponding to the credential, the phrase being generated to include words that are associated with the at least one index value in the predetermined set of associations; receiving, at the client device, a user command to output the phrase; and responsive to the user command, rendering, at the client device, the phrase corresponding to the credential. | 1. A non-transitory computer-readable medium storing instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: obtaining, at a client device, a credential identifier for a credential that is associated with a user; periodically, at a predetermined time period: obtaining, at the client device, a time derived from a timing device of the client device; determining, at the client device, at least one index value using the credential identifier and the time derived from the timing device of the client device; accessing, at the client device, a predetermined set of associations between index values and words; generating, at the client device, a phrase corresponding to the credential, the phrase being generated to include words that are associated with the at least one index value in the predetermined set of associations; receiving, at the client device, a user command to output the phrase; and responsive to the user command, rendering, at the client device, the phrase corresponding to the credential. 6. The non-transitory computer-readable medium of claim 1 , wherein obtaining, at the client device, the credential identifier for the credential that is associated with the user comprises: establishing a secure connection with a server; sending, to the server, an identifier associated with the user; and receiving, from the server, the credential identifier for the credential that is associated with the user. | 0.715076 |
7,849,091 | 15 | 19 | 15. The system of claim 14 , wherein the design module is further configured to: pack the plurality of elements of the tree-structured data, including the first set of elements and the second set of elements and the meta-data levels associated therewith, into a plurality of leaf nodes of the index structure; merge the plurality of leaf nodes of the index structure into a plurality of non-leaf nodes of the index structure until a root non-leaf node is generated; and associate the plurality of non-leaf nodes of the index structure with the explicit meta-data levels of the packed first set of elements. | 15. The system of claim 14 , wherein the design module is further configured to: pack the plurality of elements of the tree-structured data, including the first set of elements and the second set of elements and the meta-data levels associated therewith, into a plurality of leaf nodes of the index structure; merge the plurality of leaf nodes of the index structure into a plurality of non-leaf nodes of the index structure until a root non-leaf node is generated; and associate the plurality of non-leaf nodes of the index structure with the explicit meta-data levels of the packed first set of elements. 19. The system of claim 15 , the design module is further configured to associate the plurality of non-leaf nodes of the index structure with the inherited meta-data levels of the packed second set of elements. | 0.647651 |
9,311,111 | 1 | 2 | 1. A non-transitory computer-readable medium storing computer executable instructions, the instructions comprising: one or more instructions that, when executed by a processor, cause the processor to: provide a handle base class; define one or more handle subclasses, where the one or more handle subclasses have a class hierarchy that includes the handle base class; construct handle objects from the one or more handle subclasses; use the handle objects, where the handle objects are used exclusively through references to the handle objects; define one or more non-handle base classes and one or more non-handle subclasses, where the one or more non-handle subclasses have a class hierarchy that includes at least one of the one or more non-handle base classes and does not include the handle base class; construct non-handle objects from the one or more non-handle subclasses; use the non-handle objects, where the non-handle objects are used exclusively by value; store the handle objects and the non-handle objects in a memory coupled to the processor; provide a first syntax for constructing both the handle objects and the non-handle objects; and provide a second syntax for using both the handle objects and the non-handle objects. | 1. A non-transitory computer-readable medium storing computer executable instructions, the instructions comprising: one or more instructions that, when executed by a processor, cause the processor to: provide a handle base class; define one or more handle subclasses, where the one or more handle subclasses have a class hierarchy that includes the handle base class; construct handle objects from the one or more handle subclasses; use the handle objects, where the handle objects are used exclusively through references to the handle objects; define one or more non-handle base classes and one or more non-handle subclasses, where the one or more non-handle subclasses have a class hierarchy that includes at least one of the one or more non-handle base classes and does not include the handle base class; construct non-handle objects from the one or more non-handle subclasses; use the non-handle objects, where the non-handle objects are used exclusively by value; store the handle objects and the non-handle objects in a memory coupled to the processor; provide a first syntax for constructing both the handle objects and the non-handle objects; and provide a second syntax for using both the handle objects and the non-handle objects. 2. The medium of claim 1 , wherein the second syntax for using both the handle objects and the non-handle objects includes accessing properties and methods of the handle objects and the non-handle objects. | 0.746287 |
8,352,405 | 1 | 3 | 1. A non-transitory computer readable medium carrying instructions for a sentiment classifier for sentiment classification of content comprising: an aspect classifier configured to classify content as being related to a particular aspect of a plurality of aspects of information, the aspect classifier incorporating at least a portion of a domain specific sentiment lexicon to assist in classifying the content, wherein the domain specific sentiment lexicon is configured by: (i) domain specific words and/or phrases from an annotated corpus which has been filtered, (ii) domain specific words and/or phrases obtained via a search of the world wide web using a predetermined linguistic pattern and filtering the returned search results, and (iii) domain specific words and/or phrases obtained via a dictionary expansion technique performed on the domain specific words and/or phrases obtained by at least one of (i) or (ii); a polarity classifier configured to classify the content classified by the aspect classifier as having one of a positive sentiment of the particular aspect of information, a negative sentiment of the particular aspect of information or as having no sentiment of the particular aspect of information, the polarity classifier incorporating at least a portion of the domain specific sentiment lexicon to assist in classifying the content; and an aggregator configured to receive and aggregate results of predictions generated by the aspect classifier and results of predictions generated by the polarity classifier. | 1. A non-transitory computer readable medium carrying instructions for a sentiment classifier for sentiment classification of content comprising: an aspect classifier configured to classify content as being related to a particular aspect of a plurality of aspects of information, the aspect classifier incorporating at least a portion of a domain specific sentiment lexicon to assist in classifying the content, wherein the domain specific sentiment lexicon is configured by: (i) domain specific words and/or phrases from an annotated corpus which has been filtered, (ii) domain specific words and/or phrases obtained via a search of the world wide web using a predetermined linguistic pattern and filtering the returned search results, and (iii) domain specific words and/or phrases obtained via a dictionary expansion technique performed on the domain specific words and/or phrases obtained by at least one of (i) or (ii); a polarity classifier configured to classify the content classified by the aspect classifier as having one of a positive sentiment of the particular aspect of information, a negative sentiment of the particular aspect of information or as having no sentiment of the particular aspect of information, the polarity classifier incorporating at least a portion of the domain specific sentiment lexicon to assist in classifying the content; and an aggregator configured to receive and aggregate results of predictions generated by the aspect classifier and results of predictions generated by the polarity classifier. 3. The sentiment classifier of claim 1 wherein the polarity classifier further incorporates a general purpose sentiment lexicon. | 0.933679 |
9,535,900 | 8 | 13 | 8. A computing system including a processor and a memory configured to perform operations comprising: identifying content in a document of a received communication, wherein the content includes a language expression; determining a context of the language expression from a defined range of the content in the document; and generating an action item, including rendering a menu of action items, the action items including one or more of generating a reply to email, a new email, a new task, a new meeting and a chat session, generating the action item associated with the language expression based upon, at least in part, the context of the language expression, wherein the action item, when executed by a user, includes one or more excerpts from material referenced by the content in the document, the material referenced by the content in the document being distinct from the document. | 8. A computing system including a processor and a memory configured to perform operations comprising: identifying content in a document of a received communication, wherein the content includes a language expression; determining a context of the language expression from a defined range of the content in the document; and generating an action item, including rendering a menu of action items, the action items including one or more of generating a reply to email, a new email, a new task, a new meeting and a chat session, generating the action item associated with the language expression based upon, at least in part, the context of the language expression, wherein the action item, when executed by a user, includes one or more excerpts from material referenced by the content in the document, the material referenced by the content in the document being distinct from the document. 13. The computing system of claim 8 wherein the action item, when executed, includes information from the content in the document. | 0.575163 |
8,671,341 | 16 | 17 | 16. The system recited in claim 13 , further comprising claims storage configured to store the claim. | 16. The system recited in claim 13 , further comprising claims storage configured to store the claim. 17. The system recited in claim 16 , wherein the claims storage is further configured to allow a user to perform a search of the stored claim. | 0.5 |
8,560,806 | 1 | 5 | 1. A processor comprising: an interface to perform a transaction to fetch information from a memory; and memory management logic to translate an untranslated address to a memory address, including: a storage location to store a first address of an initial data structure for a first walk through a first set of translation stages; a plurality of translation stages comprising the first set of translation stages and a second set of translation stages, the first set of translation stages reserved for a first context, the second set of translation stages reserved for a second context, each translation stage of the plurality of translation stages including translation logic and a data structure, the translation logic to find a particular entry of a plurality of entries in the data structure based on a corresponding portion of the untranslated address, each entry of the plurality of entries in the data structure to store a transition indicator to indicate a context switch from the first context to the second context; and determination logic to: determine, during the first walk through the first set of translation stages, whether the particular entry of the plurality of entries in the data structure is a transition entry for the context switch from the first context to the second context based at least in part on the transition indicator of the particular entry; and in response to a determination that the particular entry is a transition entry, initiate a second walk through the second set of translation stages to cause the context switch from the first context to the second context. | 1. A processor comprising: an interface to perform a transaction to fetch information from a memory; and memory management logic to translate an untranslated address to a memory address, including: a storage location to store a first address of an initial data structure for a first walk through a first set of translation stages; a plurality of translation stages comprising the first set of translation stages and a second set of translation stages, the first set of translation stages reserved for a first context, the second set of translation stages reserved for a second context, each translation stage of the plurality of translation stages including translation logic and a data structure, the translation logic to find a particular entry of a plurality of entries in the data structure based on a corresponding portion of the untranslated address, each entry of the plurality of entries in the data structure to store a transition indicator to indicate a context switch from the first context to the second context; and determination logic to: determine, during the first walk through the first set of translation stages, whether the particular entry of the plurality of entries in the data structure is a transition entry for the context switch from the first context to the second context based at least in part on the transition indicator of the particular entry; and in response to a determination that the particular entry is a transition entry, initiate a second walk through the second set of translation stages to cause the context switch from the first context to the second context. 5. The processor of claim 1 , wherein the determination logic is also to, in response to a determination that the particular entry is a not a transition entry, continue the first walk to a succesive stage of the first set of translation stages. | 0.690355 |
9,563,282 | 5 | 6 | 5. The keyboard system in claim 1 , wherein said keyboard layout further includes a language selection key, said language selection key configured to enable selection between English language and the Indian Language. | 5. The keyboard system in claim 1 , wherein said keyboard layout further includes a language selection key, said language selection key configured to enable selection between English language and the Indian Language. 6. The keyboard system in claim 5 , wherein said language selection key is further configured to enable selection between a plurality of Indian languages. | 0.5 |
8,799,239 | 1 | 4 | 1. A method comprising: receiving a first query instruction; in response to receiving the first query instruction, determining a compression ratio of a first compression value for a first query result decision diagram and a second compression value for a compressed query result set, the first compression value being indicative of a data size of the first query result decision diagram and the second compression value being indicative of the data size of the compressed query result set; comparing the compression ratio to a threshold ratio; and causing transmission of the first query result decision diagram or causing transmission of the compressed query result set based upon a result of the comparison of the compression ratio to the threshold ratio. | 1. A method comprising: receiving a first query instruction; in response to receiving the first query instruction, determining a compression ratio of a first compression value for a first query result decision diagram and a second compression value for a compressed query result set, the first compression value being indicative of a data size of the first query result decision diagram and the second compression value being indicative of the data size of the compressed query result set; comparing the compression ratio to a threshold ratio; and causing transmission of the first query result decision diagram or causing transmission of the compressed query result set based upon a result of the comparison of the compression ratio to the threshold ratio. 4. A method according to claim 1 , wherein determining the compression ratio includes: beginning generation of the first query result decision diagram, beginning generation of the compressed query result set, and starting a timer when the compressed query result set is generated; and wherein causing transmission of the first query result decision diagram further includes causing transmission of the first query result decision diagram based on a relationship between the timer and a timer threshold. | 0.5 |
8,060,652 | 1 | 3 | 1. A system configured to transmit data packets including data formatted in a binary extensible markup language (XML), comprising: a parser configured to convert from an extensible markup language (XML) representation that is compatible with standard XML and includes element start tags, element end tags and data values to a single data stream binary representation by providing binary data representations for element start tags and data values within the XML representation and by not providing binary data representations for element end tags within the XML representation, wherein the binary data representations are each formed using X-bit bytes, and wherein consistent extensible encoding is provided for each binary data representation by using a most-significant-bit of each X-bit byte as a termination indicator bit where a first logic level indicates the byte is a termination byte and a second logic level indicates that more bytes are included in a multi-byte data word, and wherein the XML representation and the binary representation are defined according to document type definition (DTD); a data storage system; a data packager within the parser, the data packager being configured to create data packets for the single data stream binary representation that is formed using the X-bit bytes, and a first interface coupled to the parser and configured to transmit the data packets for the single data stream binary representation through a data channel to a second interface associated with a second system; wherein the element start tags are represented using positive integer binary data representations; and wherein the data values are represented using binary data representations selected from a group comprising a string, an integer, a floating point number, an enumerated value, a pattern, and a packed component. | 1. A system configured to transmit data packets including data formatted in a binary extensible markup language (XML), comprising: a parser configured to convert from an extensible markup language (XML) representation that is compatible with standard XML and includes element start tags, element end tags and data values to a single data stream binary representation by providing binary data representations for element start tags and data values within the XML representation and by not providing binary data representations for element end tags within the XML representation, wherein the binary data representations are each formed using X-bit bytes, and wherein consistent extensible encoding is provided for each binary data representation by using a most-significant-bit of each X-bit byte as a termination indicator bit where a first logic level indicates the byte is a termination byte and a second logic level indicates that more bytes are included in a multi-byte data word, and wherein the XML representation and the binary representation are defined according to document type definition (DTD); a data storage system; a data packager within the parser, the data packager being configured to create data packets for the single data stream binary representation that is formed using the X-bit bytes, and a first interface coupled to the parser and configured to transmit the data packets for the single data stream binary representation through a data channel to a second interface associated with a second system; wherein the element start tags are represented using positive integer binary data representations; and wherein the data values are represented using binary data representations selected from a group comprising a string, an integer, a floating point number, an enumerated value, a pattern, and a packed component. 3. The system of claim 1 , wherein the data values are represented using binary data representations selected from a group consisting of a string, an integer, a floating point number, an enumerated value, a pattern, and a packed component. | 0.5 |
8,266,656 | 10 | 11 | 10. The one or more non-transitory computer-readable media of claim 9 , wherein the method further comprises: receiving a revision to the plurality of search criteria; and revising the search result set corresponding to the revision. | 10. The one or more non-transitory computer-readable media of claim 9 , wherein the method further comprises: receiving a revision to the plurality of search criteria; and revising the search result set corresponding to the revision. 11. The one or more non-transitory computer-readable media of claim 10 , wherein the revision to the plurality of search criteria includes taking an action selected from the group consisting of selecting one or more additional search criteria, deselecting one or more search criteria, and combinations thereof. | 0.5 |
7,676,488 | 5 | 6 | 5. A computer program product, tangibly embodied on computer-readable storage media, the computer program product causing a data processing apparatus to: retrieve a design document from a markup language repository, the design document comprising markup language for rendering a report design and specifying at least one visual format and at least one associated condition that is specified by the markup language and that defines one or more criteria for rendering the report design according to the visual format, the criteria comprising both a logical expression pertaining to the data to be presented in the section and a description in the markup language of a visual representation to be used in rendering a report according to the report design if the logical expression is true; evaluate each logical expression of the criteria, and, if the logical expression is true, apply the visual representation described by the logical expression; apply a predefined grammar to the report design and the logical expression using a validating parser to determine whether the report design and the logical expression is syntactically correct, the predefined grammar defining a correct markup language syntax for the design and the logical expression; report any determined deviation from syntactical correctness; and render the report using data according to the report design and the at least one logical expression; and write a description of a visual representation specified in each section. | 5. A computer program product, tangibly embodied on computer-readable storage media, the computer program product causing a data processing apparatus to: retrieve a design document from a markup language repository, the design document comprising markup language for rendering a report design and specifying at least one visual format and at least one associated condition that is specified by the markup language and that defines one or more criteria for rendering the report design according to the visual format, the criteria comprising both a logical expression pertaining to the data to be presented in the section and a description in the markup language of a visual representation to be used in rendering a report according to the report design if the logical expression is true; evaluate each logical expression of the criteria, and, if the logical expression is true, apply the visual representation described by the logical expression; apply a predefined grammar to the report design and the logical expression using a validating parser to determine whether the report design and the logical expression is syntactically correct, the predefined grammar defining a correct markup language syntax for the design and the logical expression; report any determined deviation from syntactical correctness; and render the report using data according to the report design and the at least one logical expression; and write a description of a visual representation specified in each section. 6. A computer program product as in claim 5 , wherein the computer program product further causes the data processing apparatus to: retrieve the design document from a data repository via a communications network. | 0.509217 |
8,423,347 | 1 | 4 | 1. A method for managing PIM data in a user interface of a personal information management (PIM) application, comprising: receiving a first natural language entry from a user into the user interface of the personal information management (PIM) application on an electronic device, the first natural language entry includes text, the PIM application includes a plurality of types of PIM data; processing the first natural language entry to identify which type of PIM data the first natural language entry is associated with; creating a first new entry in the PIM application based on text in the first natural language entry, the first new entry is for the identified type of PIM data; receiving a second natural language entry in the interface of the PIM application, wherein the first natural language entry is maintained in the interface during said receiving the second natural language entry; processing the second natural language entry to identify which type of PIM data the second natural language entry is associated with, the determining the type of PIM data includes recognizing text in the second natural language entry; creating a second new entry in the PIM application based on the text that was recognized in the second natural language entry, the second new entry is for the identified type of PIM data; and maintaining the first and second natural language entries in the interface of the PIM application, the first and second entries are for different types of PIM data. | 1. A method for managing PIM data in a user interface of a personal information management (PIM) application, comprising: receiving a first natural language entry from a user into the user interface of the personal information management (PIM) application on an electronic device, the first natural language entry includes text, the PIM application includes a plurality of types of PIM data; processing the first natural language entry to identify which type of PIM data the first natural language entry is associated with; creating a first new entry in the PIM application based on text in the first natural language entry, the first new entry is for the identified type of PIM data; receiving a second natural language entry in the interface of the PIM application, wherein the first natural language entry is maintained in the interface during said receiving the second natural language entry; processing the second natural language entry to identify which type of PIM data the second natural language entry is associated with, the determining the type of PIM data includes recognizing text in the second natural language entry; creating a second new entry in the PIM application based on the text that was recognized in the second natural language entry, the second new entry is for the identified type of PIM data; and maintaining the first and second natural language entries in the interface of the PIM application, the first and second entries are for different types of PIM data. 4. The method of claim 1 , wherein said step of processing includes: performing preliminary parsing on the first natural language entry by code on a client computer. | 0.787371 |
9,760,634 | 18 | 20 | 18. The non-transitory computer readable medium of claim 17 , wherein the application further comprises a user interface for enabling user input. | 18. The non-transitory computer readable medium of claim 17 , wherein the application further comprises a user interface for enabling user input. 20. The non-transitory computer readable medium of claim 18 , wherein the keyword generator is further for calculating scores for a plurality of potential key word sets and the user interface receives a selection of key word sets by a user. | 0.5 |
8,880,989 | 1 | 15 | 1. A computer-implemented method of disseminating a document, the method comprising: providing a user interface display, of an authoring application, to facilitate user generation of a new document; receiving user inputs through the user interface display of the authoring application that provide document content for the document; determining that the document is a sensitive document that is subject to a data dissemination policy; and modifying the user interface display of the authoring application, while the document is being displayed, to provide a description of why the document is subject to the data dissemination policy. | 1. A computer-implemented method of disseminating a document, the method comprising: providing a user interface display, of an authoring application, to facilitate user generation of a new document; receiving user inputs through the user interface display of the authoring application that provide document content for the document; determining that the document is a sensitive document that is subject to a data dissemination policy; and modifying the user interface display of the authoring application, while the document is being displayed, to provide a description of why the document is subject to the data dissemination policy. 15. The computer-implemented method of claim 1 wherein receiving user inputs to provide document content comprises at least one of: receiving spreadsheet inputs to author a spreadsheet document; and receiving word processing inputs to author a word processing document. | 0.629477 |
6,016,395 | 1 | 32 | 1. A method for creating a computer program on a computer readable media for execution by a vector processor, the method comprising: a computer system reading a computer program written in a superset of C programming language, wherein the C programming language defines a plurality of operations and does not specify for each operation in said plurality how the operation is to be implemented in the vector processor, the computer program further including: a declaration of a value having a vector type, the vector type being part of a programming model of the vector processor, the vector type being distinct from an array type included in the C programming language; and a first operation having the vector type value as an operand, the first operation corresponding to a vector processor instruction VPI1 that can be executed by the vector processor and that has at least a vector operand; and the computer system generating one or more vector processor instructions that together implement the first operation, the one or more instructions including one or more VPI1 instructions. | 1. A method for creating a computer program on a computer readable media for execution by a vector processor, the method comprising: a computer system reading a computer program written in a superset of C programming language, wherein the C programming language defines a plurality of operations and does not specify for each operation in said plurality how the operation is to be implemented in the vector processor, the computer program further including: a declaration of a value having a vector type, the vector type being part of a programming model of the vector processor, the vector type being distinct from an array type included in the C programming language; and a first operation having the vector type value as an operand, the first operation corresponding to a vector processor instruction VPI1 that can be executed by the vector processor and that has at least a vector operand; and the computer system generating one or more vector processor instructions that together implement the first operation, the one or more instructions including one or more VPI1 instructions. 32. The method of claim 1, wherein: the declaration includes an initialization of the vector operand, the initialization being specified by use of the "=" sign, followed by a plurality of values for elements in the vector operand, the plurality of values being enclosed within the "{" and "}" signs. | 0.671429 |
8,060,505 | 2 | 4 | 2. The method of claim 1 , including: assembling the first set of documents and the second set of documents to create a third set of documents. | 2. The method of claim 1 , including: assembling the first set of documents and the second set of documents to create a third set of documents. 4. The method of claim 2 , including: extracting first structured features and unstructured features of the third set of documents, wherein the first structured features comprise author, assignee, and classification of each of the third set of documents, and documents referenced by each of the third set of documents. | 0.5 |
9,305,287 | 2 | 3 | 2. The method of claim 1 , further comprising sending the score over the network to the computing device. | 2. The method of claim 1 , further comprising sending the score over the network to the computing device. 3. The method of claim 2 wherein the suggestion includes an estimated reduction of the estimated duration if the suggestion is fulfilled. | 0.5 |
8,725,770 | 5 | 6 | 5. The method of claim 4 , wherein the at least one application provides access to said each document when the security access requirements are met. | 5. The method of claim 4 , wherein the at least one application provides access to said each document when the security access requirements are met. 6. The method of claim 5 , wherein for each document in the set of identified documents: a) the information about the content of said each document includes one or more keywords of the set of search keywords; and b) the user identity attributes meet the security access requirements, wherein said each identified document is determined to be accessible to the user based on the set of document authorization attributes stored in the index without further contacting said at least one application that provides secure access to said each identified document. | 0.5 |
9,164,737 | 1 | 2 | 1. In a computing environment, a method comprising: providing a set of metadata explicitly identifying a data type for each programming language code component of a plurality of programming language code components, wherein the plurality of programming language code components are written in a dynamically-typed programming language; detecting placement of a graphical representation of a first programming language code component on a user interface surface in a development environment, the placement graphically connecting the graphical representation of the first programming language code component to at lease one graphical representation of a second programming language component of the plurality of the programming language code components; in response to the placement, accessing a provided first set of metadata specifying a data type for the first programming language code component and validating the usage of the first programming language code component based on the date type specified by the first set metadata; and providing the first set of metadata to runtime system for enhanced type matching during execution, including inserting executable code into the first programming language component that converts one data type to an appropriate type for input or output. | 1. In a computing environment, a method comprising: providing a set of metadata explicitly identifying a data type for each programming language code component of a plurality of programming language code components, wherein the plurality of programming language code components are written in a dynamically-typed programming language; detecting placement of a graphical representation of a first programming language code component on a user interface surface in a development environment, the placement graphically connecting the graphical representation of the first programming language code component to at lease one graphical representation of a second programming language component of the plurality of the programming language code components; in response to the placement, accessing a provided first set of metadata specifying a data type for the first programming language code component and validating the usage of the first programming language code component based on the date type specified by the first set metadata; and providing the first set of metadata to runtime system for enhanced type matching during execution, including inserting executable code into the first programming language component that converts one data type to an appropriate type for input or output. 2. The method of claim 1 wherein detecting the usage of a first programming language code component comprises providing a graphical user interface for selecting and interacting with the programming language code components. | 0.757609 |
7,599,830 | 1 | 4 | 1. A method of enabling disambiguation of an input into a handheld electronic device, the handheld electronic device including an input apparatus, an output apparatus, and a memory having a plurality of objects stored therein, the plurality of objects including a plurality of language objects and a plurality of frequency objects, each of at least a portion of the language objects of the plurality of language objects being associated with an associated frequency object of the plurality of frequency objects, the handheld electronic device having a number of messages available thereon, each message of at least a portion of the number of messages including a number of language objects, the input apparatus including a plurality of input members, each of at least a portion of the input members of the plurality of input members having a plurality of linguistic elements assigned thereto, the method comprising: detecting at least one of a replying input and a forwarding input with respect to a message of the number of messages; detecting an ambiguous input including a number of input member actuations of a number of the input members of the plurality of input members, each of at least a portion of the input members of the number of input members including a number of linguistic elements assigned thereto, at least one of the input members of the number of input members having a plurality of linguistic elements assigned thereto; determining that a first portion of the memory is associated with the message, the first portion of the memory including at least a portion of the language objects of the number of language objects of the message; identifying in the first portion of the memory a first language object that corresponds with the ambiguous input; and outputting at least a portion of the first language object as a first proposed disambiguation of the ambiguous input. | 1. A method of enabling disambiguation of an input into a handheld electronic device, the handheld electronic device including an input apparatus, an output apparatus, and a memory having a plurality of objects stored therein, the plurality of objects including a plurality of language objects and a plurality of frequency objects, each of at least a portion of the language objects of the plurality of language objects being associated with an associated frequency object of the plurality of frequency objects, the handheld electronic device having a number of messages available thereon, each message of at least a portion of the number of messages including a number of language objects, the input apparatus including a plurality of input members, each of at least a portion of the input members of the plurality of input members having a plurality of linguistic elements assigned thereto, the method comprising: detecting at least one of a replying input and a forwarding input with respect to a message of the number of messages; detecting an ambiguous input including a number of input member actuations of a number of the input members of the plurality of input members, each of at least a portion of the input members of the number of input members including a number of linguistic elements assigned thereto, at least one of the input members of the number of input members having a plurality of linguistic elements assigned thereto; determining that a first portion of the memory is associated with the message, the first portion of the memory including at least a portion of the language objects of the number of language objects of the message; identifying in the first portion of the memory a first language object that corresponds with the ambiguous input; and outputting at least a portion of the first language object as a first proposed disambiguation of the ambiguous input. 4. The method of claim 1 , further comprising making a comparison between at least a portion of the message and a first entry in a lookup table in the memory, and employing the first entry in said determining that a first portion of the memory is associated with the message. | 0.879492 |
9,786,268 | 4 | 6 | 4. The method of claim 3 , further comprising: capturing the related information and locating the related information on an associated video stored in the one or more devices and the social media website. | 4. The method of claim 3 , further comprising: capturing the related information and locating the related information on an associated video stored in the one or more devices and the social media website. 6. The method of claim 4 , further comprising: determining whether the device is a mobile phone or a computer system; and accessing a file system of the device based on whether the device is the mobile phone or the computer system. | 0.800862 |
7,900,134 | 10 | 12 | 10. A method of providing a user interface comprising: considering multiple parameters one of which includes an XSL-T file; and based upon the considered parameters, rendering a user interface sufficient to enable a user to interact with a DHTML view that has been rendered from an XML document using a crystal, the crystal containing one or more behaviors and at least one XSL-T file; and receiving, via the user interface, a user interaction with the DHTML view; and mapping, via the one or more behaviors, the user interaction to the XML document. | 10. A method of providing a user interface comprising: considering multiple parameters one of which includes an XSL-T file; and based upon the considered parameters, rendering a user interface sufficient to enable a user to interact with a DHTML view that has been rendered from an XML document using a crystal, the crystal containing one or more behaviors and at least one XSL-T file; and receiving, via the user interface, a user interaction with the DHTML view; and mapping, via the one or more behaviors, the user interaction to the XML document. 12. The method of claim 10 , wherein one parameter comprises a portion of an XML schema that corresponds to a user's selection. | 0.737603 |
6,122,666 | 7 | 8 | 7. In a network comprising a plurality of source servers, each associated with sales information, a plurality of clients each making requests for said sales information, wherein each client request corresponds to one of a plurality of users and a plurality of proxies which receive said requests for sales information from said clients, a method of satisfying said requests for sales information, comprising: dividing said plurality of proxies into a plurality of sets of one or more proxies wherein each of the plurality of sets of one or more proxies performs a respectively different translation based on a preassignment; directing a first translation request to a first set of one or more proxies based on said preassignment; directing a second translation request to a second set of one or more proxies based on said preassignment; performing said first translation at said first set of one or more proxies after receiving said sales information from one of said source servers; performing said second translation at said second set of one or more proxies after receiving said sales information from one or another of said source servers; and providing said first and second translations. | 7. In a network comprising a plurality of source servers, each associated with sales information, a plurality of clients each making requests for said sales information, wherein each client request corresponds to one of a plurality of users and a plurality of proxies which receive said requests for sales information from said clients, a method of satisfying said requests for sales information, comprising: dividing said plurality of proxies into a plurality of sets of one or more proxies wherein each of the plurality of sets of one or more proxies performs a respectively different translation based on a preassignment; directing a first translation request to a first set of one or more proxies based on said preassignment; directing a second translation request to a second set of one or more proxies based on said preassignment; performing said first translation at said first set of one or more proxies after receiving said sales information from one of said source servers; performing said second translation at said second set of one or more proxies after receiving said sales information from one or another of said source servers; and providing said first and second translations. 8. A method of satisfying said requests for sales information according to claim 7, wherein said translation is a language translation. | 0.614286 |
7,634,469 | 4 | 5 | 4. A computer-based method for searching information and displaying search results, the method comprising: receiving one or more keywords input from one or more client computers; obtaining search results according to the one or more keywords from a cache of the search server or from an index database, the search results comprising one or more documents; calculating a weight of each word of the documents in the search results; confirming at least one cluster name according to the search results by comparing each weight and a defined cluster-name threshold, selecting the words that reach the defined cluster-name threshold, and deleting punctuations in the words that reach the defined cluster-name threshold according to a longest-word principle; calculating a correlation between each cluster name and each document in the search results; clustering each of the one or more documents in the search results into a corresponding cluster name according to the correlation; calculating a probability of each document occurring in each language module; classifying each document in the search results into a corresponding field according to the probability, and thus obtaining classified search results; generating a cluster diagram according to the at least one cluster name and the clustered documents, and generating a cluster-classification diagram according to the classified search results and the generated cluster diagram; and outputting the generated cluster-classification diagram to the one or more client computers. | 4. A computer-based method for searching information and displaying search results, the method comprising: receiving one or more keywords input from one or more client computers; obtaining search results according to the one or more keywords from a cache of the search server or from an index database, the search results comprising one or more documents; calculating a weight of each word of the documents in the search results; confirming at least one cluster name according to the search results by comparing each weight and a defined cluster-name threshold, selecting the words that reach the defined cluster-name threshold, and deleting punctuations in the words that reach the defined cluster-name threshold according to a longest-word principle; calculating a correlation between each cluster name and each document in the search results; clustering each of the one or more documents in the search results into a corresponding cluster name according to the correlation; calculating a probability of each document occurring in each language module; classifying each document in the search results into a corresponding field according to the probability, and thus obtaining classified search results; generating a cluster diagram according to the at least one cluster name and the clustered documents, and generating a cluster-classification diagram according to the classified search results and the generated cluster diagram; and outputting the generated cluster-classification diagram to the one or more client computers. 5. The method according to claim 4 , before calculating a weight of each word of the documents in the search results, the method further comprising: preprocessing the search results, the preprocessing comprising defining thresholds, the thresholds comprising the cluster-name threshold and a correlation threshold. | 0.615196 |
8,311,999 | 1 | 4 | 1. A computer-based method of knowledge research and mapping, the method comprising: providing at least one computer processor coupled to at least one non-transitory storage medium, the at least one computer processor performing a set of processing tasks, including: generating a research knowledge map using an entity-relationship model comprising entity-relationship-entity triplets, including representing topics determined from the one or more queries as entities and determining relationships between entities from an informational taxonomy; receiving a query related to a domain of research; storing the query in the research knowledge map in the at least one computer storage medium; automatically submitting the query to one or more knowledge bases; filtering one or more responses to the query into response relationship subsets; and linking one or more of the responses from the response relationship subsets to the stored query in the research knowledge map, wherein the knowledge map provides interrelated information for one or more queries within the domain of research. | 1. A computer-based method of knowledge research and mapping, the method comprising: providing at least one computer processor coupled to at least one non-transitory storage medium, the at least one computer processor performing a set of processing tasks, including: generating a research knowledge map using an entity-relationship model comprising entity-relationship-entity triplets, including representing topics determined from the one or more queries as entities and determining relationships between entities from an informational taxonomy; receiving a query related to a domain of research; storing the query in the research knowledge map in the at least one computer storage medium; automatically submitting the query to one or more knowledge bases; filtering one or more responses to the query into response relationship subsets; and linking one or more of the responses from the response relationship subsets to the stored query in the research knowledge map, wherein the knowledge map provides interrelated information for one or more queries within the domain of research. 4. The method according to claim 1 , wherein submitting the query to one or more knowledge bases comprises submitting the query to a knowledge search engine and automatically formatting the query to be compatible with the knowledge search engine. | 0.588629 |
8,074,166 | 1 | 4 | 1. A method for performing focus inference when compiling an Extensible Markup Language Transforms (XSLT) stylesheet into a compiled XSLT processor, comprising: generating an Abstract Syntax Tree (AST) from said XSLT stylesheet; annotating nodes in said AST that are associated with variables and parameters with focus inference flags, said annotating comprising for each of said nodes determining which of a plurality of focus inference flags that define a focus is required to be maintained; building a reverse call graph for a template associated with the XSLT stylesheet; propagating any focus inference flags from a callee template to a caller template; propagating any focus inference flags through the reverse call graph; and using the focus defined by the focus inference flags directly in one or more of a code generator in an XSLT compilation architecture, an interpreter, and/or a JITer, wherein said focus inference flags comprise a “current†focus inference flag, a “position†focus inference flag, and a “last†focus inference flag. | 1. A method for performing focus inference when compiling an Extensible Markup Language Transforms (XSLT) stylesheet into a compiled XSLT processor, comprising: generating an Abstract Syntax Tree (AST) from said XSLT stylesheet; annotating nodes in said AST that are associated with variables and parameters with focus inference flags, said annotating comprising for each of said nodes determining which of a plurality of focus inference flags that define a focus is required to be maintained; building a reverse call graph for a template associated with the XSLT stylesheet; propagating any focus inference flags from a callee template to a caller template; propagating any focus inference flags through the reverse call graph; and using the focus defined by the focus inference flags directly in one or more of a code generator in an XSLT compilation architecture, an interpreter, and/or a JITer, wherein said focus inference flags comprise a “current†focus inference flag, a “position†focus inference flag, and a “last†focus inference flag. 4. The method of claim 1 , wherein said propagating any focus inference flags through the reverse call graph is conducted by a fixed-point algorithm on a control-flow graph. | 0.542328 |
7,941,426 | 7 | 8 | 7. A computer readable storage medium containing a program which, when executed, performs an operation, comprising: receiving a database query; generating a plurality of query plans for executing the database query; estimating one or more characteristics of energy consumption for executing each query plan; estimating one or more characteristics of time for executing each query plan; and selecting one of the plurality of query plans for executing the database query, based at least on (i) the one or more characteristics of energy consumption, (ii) the one or more characteristics of time, and (iii) a relative priority between the characteristics of energy consumption and the characteristics of time. | 7. A computer readable storage medium containing a program which, when executed, performs an operation, comprising: receiving a database query; generating a plurality of query plans for executing the database query; estimating one or more characteristics of energy consumption for executing each query plan; estimating one or more characteristics of time for executing each query plan; and selecting one of the plurality of query plans for executing the database query, based at least on (i) the one or more characteristics of energy consumption, (ii) the one or more characteristics of time, and (iii) a relative priority between the characteristics of energy consumption and the characteristics of time. 8. The computer readable storage medium of claim 7 , the operation further comprising: executing the selected query plan; and returning a set of query results. | 0.652838 |
9,418,310 | 1 | 9 | 1. A method comprising: receiving a content item containing an image, the image including text; performing connected component analysis on the image to identify connected components of the image based at least in part on comparing a value of a pixel property for a particular pixel with a value of the pixel property for a neighboring pixel; classifying individual ones of the connected components of the image as text components or non-text components based at least on a text identification classifier; training a legibility classifier using one or more images of training data; determining a legibility threshold based at least in part on a determined legibility of the one or more images of the training data; determining a legibility of the individual ones of the text components by: generating, using the legibility classifier, a confidence level for the legibility of an individual text component based at least in part on one or more features of the individual text component in the image; and comparing the confidence level with the legibility threshold; classifying, based at least in part on the determining of the legibility of the individual ones of the text components, the image as illegible; and sending a message indicating that the image is illegible. | 1. A method comprising: receiving a content item containing an image, the image including text; performing connected component analysis on the image to identify connected components of the image based at least in part on comparing a value of a pixel property for a particular pixel with a value of the pixel property for a neighboring pixel; classifying individual ones of the connected components of the image as text components or non-text components based at least on a text identification classifier; training a legibility classifier using one or more images of training data; determining a legibility threshold based at least in part on a determined legibility of the one or more images of the training data; determining a legibility of the individual ones of the text components by: generating, using the legibility classifier, a confidence level for the legibility of an individual text component based at least in part on one or more features of the individual text component in the image; and comparing the confidence level with the legibility threshold; classifying, based at least in part on the determining of the legibility of the individual ones of the text components, the image as illegible; and sending a message indicating that the image is illegible. 9. The method as recited in claim 1 , further comprising using the legibility classifier for performing classifying the image as illegible. | 0.931324 |
10,157,610 | 1 | 13 | 1. A computer-implemented method for training acoustic models in an automatic speech recognition system through a selection of acoustic data comprising: training a first acoustic model in the automatic speech recognition system using a training-data corpus comprising a plurality of speech audio files and a respective plurality of transcriptions for the plurality of speech audio files; performing a forced Viterbi alignment of the plurality of speech audio files using the trained first acoustic model in the automatic speech recognition system; calculating a global frame likelihood score δ for the plurality of speech audio files, wherein the global frame likelihood score δ comprises an average of frame likelihoods over the training-data corpus; creating a first subset of the training-data corpus comprising one or more audio files by selecting the one or more audio files from the plurality of speech audio files based on the global frame likelihood score δ; performing a phoneme recognition of the plurality of speech audio files using the trained first acoustic model and the respective plurality of transcriptions in the automatic speech recognition system; calculating a global phoneme recognition accuracy ν for the plurality of speech audio files; creating a second subset of the training-data corpus comprising audio files retained from the one or more audio files of the first subset of the training-data corpus which meet at least one predetermined criterion indicating that an audio file has good audio quality; and training a second acoustic model in the automatic speech recognition system using the second subset of the training-data corpus. | 1. A computer-implemented method for training acoustic models in an automatic speech recognition system through a selection of acoustic data comprising: training a first acoustic model in the automatic speech recognition system using a training-data corpus comprising a plurality of speech audio files and a respective plurality of transcriptions for the plurality of speech audio files; performing a forced Viterbi alignment of the plurality of speech audio files using the trained first acoustic model in the automatic speech recognition system; calculating a global frame likelihood score δ for the plurality of speech audio files, wherein the global frame likelihood score δ comprises an average of frame likelihoods over the training-data corpus; creating a first subset of the training-data corpus comprising one or more audio files by selecting the one or more audio files from the plurality of speech audio files based on the global frame likelihood score δ; performing a phoneme recognition of the plurality of speech audio files using the trained first acoustic model and the respective plurality of transcriptions in the automatic speech recognition system; calculating a global phoneme recognition accuracy ν for the plurality of speech audio files; creating a second subset of the training-data corpus comprising audio files retained from the one or more audio files of the first subset of the training-data corpus which meet at least one predetermined criterion indicating that an audio file has good audio quality; and training a second acoustic model in the automatic speech recognition system using the second subset of the training-data corpus. 13. The method of claim 1 , further comprising using a mathematical equation δ = ∑ r = 1 R β r R to obtain the global frame likelihood score δ, wherein β r is an average frame likelihood score and R is the total number of the plurality of speech audio files. | 0.694639 |
9,892,273 | 6 | 11 | 6. A method for providing controlled delivery of multi-class content to a user, the method comprising the steps of: receiving a content item directed towards an intended recipient from a content source via a secure communication channel through a security firewall, wherein the secure communication channel enables the content and the content source to be trusted; identifying a classification level of the content item; and determining the content item is a first content item to be received for the intended recipient, and when the content item is the first content item: creating a URL that includes a unique identifier identifying the intended recipient and a content source providing the first content item; creating an XML index file that is accessible via the URL to establish a specific RSS feed limited to the intended recipient and the content source for communicating to the intended recipient each of a plurality of different content items of the content source directed to the intended recipient; placing at least a portion of content of the content item within an associated entry in the XML index file; creating an access controlled HTML or XML content file containing a portion of the content of the content item; and placing a link to the access controlled HTML or XML content file iii the associated entry in the XML index file; and accessing, using an RSS reader processing the URL, the content items of the content source for the intended recipient is via the specific RSS feed limited to the intended recipient and the content source. | 6. A method for providing controlled delivery of multi-class content to a user, the method comprising the steps of: receiving a content item directed towards an intended recipient from a content source via a secure communication channel through a security firewall, wherein the secure communication channel enables the content and the content source to be trusted; identifying a classification level of the content item; and determining the content item is a first content item to be received for the intended recipient, and when the content item is the first content item: creating a URL that includes a unique identifier identifying the intended recipient and a content source providing the first content item; creating an XML index file that is accessible via the URL to establish a specific RSS feed limited to the intended recipient and the content source for communicating to the intended recipient each of a plurality of different content items of the content source directed to the intended recipient; placing at least a portion of content of the content item within an associated entry in the XML index file; creating an access controlled HTML or XML content file containing a portion of the content of the content item; and placing a link to the access controlled HTML or XML content file iii the associated entry in the XML index file; and accessing, using an RSS reader processing the URL, the content items of the content source for the intended recipient is via the specific RSS feed limited to the intended recipient and the content source. 11. The method of claim 6 , wherein the step of creating a URL that includes a unique identifier further comprises incorporating a classification of the XML index file into the URL. | 0.880607 |
8,055,758 | 13 | 16 | 13. One or more machine-readable media comprising instructions for execution by a device embedded in an apparatus to report a state of the apparatus to a remote computer, the instructions for causing the device to: detect the state of the apparatus; generate a message that reports the state of the apparatus to the remote computer, the message comprising a HyperText Transfer Protocol (HTTP) command, the message using eXtensible Markup Language (XML) to report the state, the message containing a code that is unique to the device or apparatus, wherein generating is performed periodically or in response to a deviation in the state; and send the message comprising the HTTP command to the remote computer, the HTTP command comprising a command that is configured to report the state of the apparatus using XML; wherein the device is on an internal network and the remote computer is on an external network that is separate from the internal network, and wherein, as a result, the remote computer cannot communicate to the device to obtain the state of the apparatus; and wherein the state of the apparatus comprises values of two or more variables associated with the apparatus, one or more of the variables being flagged if one or more of the variables corresponds to an error condition associated with the apparatus. | 13. One or more machine-readable media comprising instructions for execution by a device embedded in an apparatus to report a state of the apparatus to a remote computer, the instructions for causing the device to: detect the state of the apparatus; generate a message that reports the state of the apparatus to the remote computer, the message comprising a HyperText Transfer Protocol (HTTP) command, the message using eXtensible Markup Language (XML) to report the state, the message containing a code that is unique to the device or apparatus, wherein generating is performed periodically or in response to a deviation in the state; and send the message comprising the HTTP command to the remote computer, the HTTP command comprising a command that is configured to report the state of the apparatus using XML; wherein the device is on an internal network and the remote computer is on an external network that is separate from the internal network, and wherein, as a result, the remote computer cannot communicate to the device to obtain the state of the apparatus; and wherein the state of the apparatus comprises values of two or more variables associated with the apparatus, one or more of the variables being flagged if one or more of the variables corresponds to an error condition associated with the apparatus. 16. The one or more Non-transitory machine-readable media of claim 13 , further comprising instructions that cause the device to: determine the deviation in the state. | 0.773713 |
8,126,220 | 7 | 10 | 7. A computer program product for annotating a stimulus, the computer program product comprising a non-transitory computer usable medium having computer readable program means for causing a computer to perform the steps of: detecting a plurality of facial expressions in an audience of the stimulus; interpreting the facial expressions to estimate a mood for a time period of the stimulus, wherein interpreting the facial expressions comprises: classifying each of the facial expressions as corresponding to an emotion from a set of emotions; and statistically analyzing the respective emotions corresponding to the plurality of facial expressions to estimate the mood; generating an annotation of the stimulus based on the mood estimated; repeating the detecting, interpreting, and generating steps to produce a plurality of the annotations that respectively correspond to different time periods of the stimulus; and indexing the annotations according to the respective moods, wherein the indexing provides a two-way linkage between the annotations and the time periods of the stimulus. | 7. A computer program product for annotating a stimulus, the computer program product comprising a non-transitory computer usable medium having computer readable program means for causing a computer to perform the steps of: detecting a plurality of facial expressions in an audience of the stimulus; interpreting the facial expressions to estimate a mood for a time period of the stimulus, wherein interpreting the facial expressions comprises: classifying each of the facial expressions as corresponding to an emotion from a set of emotions; and statistically analyzing the respective emotions corresponding to the plurality of facial expressions to estimate the mood; generating an annotation of the stimulus based on the mood estimated; repeating the detecting, interpreting, and generating steps to produce a plurality of the annotations that respectively correspond to different time periods of the stimulus; and indexing the annotations according to the respective moods, wherein the indexing provides a two-way linkage between the annotations and the time periods of the stimulus. 10. The computer program product of claim 7 , wherein determining a mood comprises: analyzing the plurality of facial expressions; and classifying real time emotional responses from the plurality of facial expressions. | 0.5 |
7,953,600 | 31 | 32 | 31. The system of claim 20 wherein the source other than the target voice corpus comprises a shared corpus that includes speech units recorded from a different human speaker than the human speaker used to record the target voice corpus, and wherein the shared corpus is configured to be used in synthesizing multiple different target voices. | 31. The system of claim 20 wherein the source other than the target voice corpus comprises a shared corpus that includes speech units recorded from a different human speaker than the human speaker used to record the target voice corpus, and wherein the shared corpus is configured to be used in synthesizing multiple different target voices. 32. The system of claim 31 wherein the shared corpus further includes synthesized speech units. | 0.860294 |
9,047,278 | 22 | 26 | 22. A non-transitory computer storage medium storing a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: identifying queries in query data; determining, in each of the queries, (i) an entity-descriptive portion that refers to an entity and (ii) a suffix; determining query counts of a number of times that the respective queries were submitted; for at least a particular query of the identified queries, distributing the query count for the particular query among multiple different entities by assigning, to each of the multiple different entities, a partial query count that is an estimate of a number of submissions of the particular query that refer to the entity; estimating, based at least in part on one or more of the partial query counts, an entity-level count of query submissions that include a particular suffix and are considered to refer to a first entity of the multiple different entities; determining that the first entity is a particular type of entity; determining a type-level count of the query submissions that include the particular suffix and are estimated to refer to entities of the particular type of entity; and assigning, based on the entity-level count and the type-level count, a score for the particular suffix with respect to the first entity. | 22. A non-transitory computer storage medium storing a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: identifying queries in query data; determining, in each of the queries, (i) an entity-descriptive portion that refers to an entity and (ii) a suffix; determining query counts of a number of times that the respective queries were submitted; for at least a particular query of the identified queries, distributing the query count for the particular query among multiple different entities by assigning, to each of the multiple different entities, a partial query count that is an estimate of a number of submissions of the particular query that refer to the entity; estimating, based at least in part on one or more of the partial query counts, an entity-level count of query submissions that include a particular suffix and are considered to refer to a first entity of the multiple different entities; determining that the first entity is a particular type of entity; determining a type-level count of the query submissions that include the particular suffix and are estimated to refer to entities of the particular type of entity; and assigning, based on the entity-level count and the type-level count, a score for the particular suffix with respect to the first entity. 26. The computer storage medium of claim 22 , wherein the operations further comprise: based on the score assigned to the particular suffix, selecting an attribute corresponding to the particular suffix as an attribute for the first entity; receiving a query submission that refers to the first entity; and in response to receiving the query submission that refers to the first entity, providing data that identifies the attribute and a value of the attribute for the first entity. | 0.50616 |
8,910,120 | 10 | 11 | 10. The process of claim 7 , wherein said software bug description query comprises structured and unstructured data. | 10. The process of claim 7 , wherein said software bug description query comprises structured and unstructured data. 11. The process of claim 10 , wherein said structured and unstructured data comprises one or more of the following items: natural language text; or textual rendering of core dumps; or debugger output; or a state of the computer on which the software being debugged resides; or information in a current software bug report; or information obtained from a user's interaction with a debugger. | 0.5 |
7,860,886 | 1 | 4 | 1. A computerized method for providing query results based at least in part on user intent, comprising: receiving, at a computing device, a query from each of a plurality of users, each query of queries received from the plurality of users being a same query; generating and providing query results to each user of the plurality of users at least in part in response to the receiving of the query; identifying actions taken by said each user of the plurality of users upon receiving the query results to determine query-related behavior of the plurality of users after submitting the query by identifying patterns in the actions that evince a predominant intent of the users in entering the queries; associating a result-generating function with the query based at least in part on the determined query-related behavior of the plurality of users after submitting the query; receiving the query from an individual user, the query received from the individual user being the same query previously submitted by said each user of the plurality of users; identifying, at least in part in response to the receiving of the query from the individual user and using classification mapping information, the result-generating function associated with the query, wherein the classification mapping information maps queries into different result-generating functions based on an analysis of prior query-related behavior of a plurality of users; and generating query results for the individual user using the identified result-generating function that is based at least in part on the determined query-related behavior of the plurality of users that have submitted the query. | 1. A computerized method for providing query results based at least in part on user intent, comprising: receiving, at a computing device, a query from each of a plurality of users, each query of queries received from the plurality of users being a same query; generating and providing query results to each user of the plurality of users at least in part in response to the receiving of the query; identifying actions taken by said each user of the plurality of users upon receiving the query results to determine query-related behavior of the plurality of users after submitting the query by identifying patterns in the actions that evince a predominant intent of the users in entering the queries; associating a result-generating function with the query based at least in part on the determined query-related behavior of the plurality of users after submitting the query; receiving the query from an individual user, the query received from the individual user being the same query previously submitted by said each user of the plurality of users; identifying, at least in part in response to the receiving of the query from the individual user and using classification mapping information, the result-generating function associated with the query, wherein the classification mapping information maps queries into different result-generating functions based on an analysis of prior query-related behavior of a plurality of users; and generating query results for the individual user using the identified result-generating function that is based at least in part on the determined query-related behavior of the plurality of users that have submitted the query. 4. The computerized method of claim 1 , wherein the actions comprise at least one click-through event in which a user clicks on an item. | 0.89881 |
10,013,612 | 12 | 13 | 12. The computer program product of claim 9 wherein the instructions are executable by the processor to identify similarity feature sets from a plurality of features derived from digital representations of a plurality of image captures, the plurality of features being represented in a feature space corresponding to a recognition algorithm, and the similarity feature sets being selected based on a similarity measure. | 12. The computer program product of claim 9 wherein the instructions are executable by the processor to identify similarity feature sets from a plurality of features derived from digital representations of a plurality of image captures, the plurality of features being represented in a feature space corresponding to a recognition algorithm, and the similarity feature sets being selected based on a similarity measure. 13. The computer program product of claim 12 wherein the similarity measure includes at least one of the following: a Euclidean distance, a Mahalanobis distance, a Hamming distance and a feature space variance. | 0.623656 |
7,747,980 | 1 | 7 | 1. A method for forming and assembling an individual self-contained pre-linked cross-device software application as an application package, each application package or portion of an application package is adapted to execute on an interoperability engine in a device and to distribute the application package or a portion of the application package to other interoperability engines in other devices over a communications link, the other devices being formed into unified teams for cooperative execution over a plurality of the teamed devices, the method comprising: forming the application package from source materials which encapsulate a main application function code portion, a main application data portion, any optional binary encoded parts portion, and a discovery and distribution code portion; and encoding the application package portions into a linear binary data structure of addressable parts wherein the application package includes self-contained and pre-linked elements; the discovery and distribution code portion encoded to be operable during execution to discover capabilities and resources of a device and then to distribute executable sub-units of the application package over one or more communication links to other devices so that the distributed executable sub-units execute on a team of devices that are unified by the distributed executable sub-units to carry out the function of the application where each device in said team of devices is running a unification engine adapted for executing at least the distributed executable sub-units of the application; each said linear binary data structure including: (i) exactly one linear main program code part including coded instructions where the addresses of all the coded instructions are located in one linear consecutive address space, and (ii) exactly one linear main program data part including data elements and where the addresses of all the data elements are located in one linear consecutive address space; the linear binary data structure including two or more executable sub-units made up of exactly one linear contiguous subset of the main program code part and exactly one linear contiguous subset of the main program data part, along with zero or more of said optional binary encoded parts; and wherein all the code that embodies and carries out the function of the software application on all said teamed devices is contained in the original application package data structure before being distributed to the teamed devices. | 1. A method for forming and assembling an individual self-contained pre-linked cross-device software application as an application package, each application package or portion of an application package is adapted to execute on an interoperability engine in a device and to distribute the application package or a portion of the application package to other interoperability engines in other devices over a communications link, the other devices being formed into unified teams for cooperative execution over a plurality of the teamed devices, the method comprising: forming the application package from source materials which encapsulate a main application function code portion, a main application data portion, any optional binary encoded parts portion, and a discovery and distribution code portion; and encoding the application package portions into a linear binary data structure of addressable parts wherein the application package includes self-contained and pre-linked elements; the discovery and distribution code portion encoded to be operable during execution to discover capabilities and resources of a device and then to distribute executable sub-units of the application package over one or more communication links to other devices so that the distributed executable sub-units execute on a team of devices that are unified by the distributed executable sub-units to carry out the function of the application where each device in said team of devices is running a unification engine adapted for executing at least the distributed executable sub-units of the application; each said linear binary data structure including: (i) exactly one linear main program code part including coded instructions where the addresses of all the coded instructions are located in one linear consecutive address space, and (ii) exactly one linear main program data part including data elements and where the addresses of all the data elements are located in one linear consecutive address space; the linear binary data structure including two or more executable sub-units made up of exactly one linear contiguous subset of the main program code part and exactly one linear contiguous subset of the main program data part, along with zero or more of said optional binary encoded parts; and wherein all the code that embodies and carries out the function of the software application on all said teamed devices is contained in the original application package data structure before being distributed to the teamed devices. 7. The method of claim 1 , wherein the software application package format includes: a signature portion; a keywords portion; a parts portion; a part table portion; and a trailer portion containing the offset of the part table from the beginning of the package file. | 0.926479 |
9,818,405 | 7 | 11 | 7. The method according to claim 1 , wherein, the computer is capable of announcing a given text or a given record to the user according to the conducted operation. | 7. The method according to claim 1 , wherein, the computer is capable of announcing a given text or a given record to the user according to the conducted operation. 11. The method according to claim 7 , wherein an announcement database is created for a plurality of customer segments; wherein the plurality of customer segments are categorized according to age, education, and demography of customers; wherein for the same conducted operation, the announcement corresponding to the customer segment in which the user falls is played from the announcement database. | 0.5 |
10,007,965 | 13 | 14 | 13. The computing-implemented method of claim 11 , comprising: identifying one or more conditional statements in the compiled shader; and determining whether one or more portions of the compiled shader can be patched based on the identified one or more conditional statements. | 13. The computing-implemented method of claim 11 , comprising: identifying one or more conditional statements in the compiled shader; and determining whether one or more portions of the compiled shader can be patched based on the identified one or more conditional statements. 14. The computing-implemented method of claim 13 , comprising replacing the one or more identified conditional statements with one or more unconditional statements, wherein the one or more unconditional statements correspond to values of one or more global constants from the global constant buffer. | 0.5 |
8,793,235 | 13 | 15 | 13. A non-transitory computer readable storage medium comprising instructions that, when executed by a processor, perform a method comprising: sending a search query to a search engine; receiving a set of search results responsive to the search query, the set of search results comprising at least one prerender instruction indicating at least one of the search results is a candidate for prerendering; identifying the at least one prerender instruction, wherein the at least one prerender instruction is identified using an indication, the indication comprising at least one of: an amount of traffic flowing from the search engine to the at least one search result, a location of a client device that provided the search query, or a size of one or more resources associated with the at least one search result; and prerendering the at least one search result associated with the at least one prerender instruction for loading the search result into a hidden browser instance. | 13. A non-transitory computer readable storage medium comprising instructions that, when executed by a processor, perform a method comprising: sending a search query to a search engine; receiving a set of search results responsive to the search query, the set of search results comprising at least one prerender instruction indicating at least one of the search results is a candidate for prerendering; identifying the at least one prerender instruction, wherein the at least one prerender instruction is identified using an indication, the indication comprising at least one of: an amount of traffic flowing from the search engine to the at least one search result, a location of a client device that provided the search query, or a size of one or more resources associated with the at least one search result; and prerendering the at least one search result associated with the at least one prerender instruction for loading the search result into a hidden browser instance. 15. The non-transitory computer readable medium of claim 13 , wherein the instructions further comprise: storing metrics associated with a selection of a selected search result from the set of search result; and transmitting the metrics to provide statistical data to improve selection of prerendering candidates in response to subsequent search queries. | 0.5 |
8,799,262 | 12 | 18 | 12. A method for performing a user-configured web crawl, comprising: receiving a user-specified web crawl configuration for crawling a web to inspect text of resources accessible on the web, each resource identified by a unique uniform resource locator (URL), the user-specified web crawl configuration comprising user-specified crawling rules specifying crawling behavior, maintaining a queue of unprocessed URLs of resources; retrieving from the queue a next unprocessed URL; retrieving the crawling rules for the retrieved URL, the crawling rules specifying crawling behavior for at least one each of a general crawl behavior, one or more page-specific crawl behavior to be applied during a crawl to one or more identified pages, and one or more element-specific crawl behavior to be applied during a crawl to one or more identified page elements; if allowed by the specified general crawl behavior and page-specific crawl behavior of the retrieved crawling rules, fetching the page resource addressed by the retrieved URL; processing the fetched page resource on an element-by-element basis, by parsing a next page element from the fetched page resource, and if an element-specific behavior is specified in the retrieved crawling rules for the parsed next page element then operating with regard to the element according to the specified element-specific behavior, and otherwise if a page-specific behavior is specified for the fetched page resource then operating with regard to the element according to the specified page-specific behavior, and otherwise if a global crawl behavior is specified then operating with regard to the element according to the specified global crawl behavior, and otherwise operating with regard to the element according to a default crawl behavior; and repeating the processing until either all elements have been parsed and processed in accordance with the retrieved crawling rules, and wherein the default crawl behavior comprises extracting URLs of outbound links and adding the extracted URLs to the queue, storing text to a resource repository for further analysis; and repeating the steps of retrieving the next unprocessed URL through this repeating step until the queue is empty of unprocessed URLs; and wherein the retrieved crawling rules define the crawling behavior in terms of whether to record the resource text, whether to follow hyperlinks of the resource, whether to record text description in metadata associated with the page, whether to record keywords identified in the metadata associated with the page, whether to override a page title element, whether to exclude one or more identified resource pages, whether to exclude one or more identified domains. | 12. A method for performing a user-configured web crawl, comprising: receiving a user-specified web crawl configuration for crawling a web to inspect text of resources accessible on the web, each resource identified by a unique uniform resource locator (URL), the user-specified web crawl configuration comprising user-specified crawling rules specifying crawling behavior, maintaining a queue of unprocessed URLs of resources; retrieving from the queue a next unprocessed URL; retrieving the crawling rules for the retrieved URL, the crawling rules specifying crawling behavior for at least one each of a general crawl behavior, one or more page-specific crawl behavior to be applied during a crawl to one or more identified pages, and one or more element-specific crawl behavior to be applied during a crawl to one or more identified page elements; if allowed by the specified general crawl behavior and page-specific crawl behavior of the retrieved crawling rules, fetching the page resource addressed by the retrieved URL; processing the fetched page resource on an element-by-element basis, by parsing a next page element from the fetched page resource, and if an element-specific behavior is specified in the retrieved crawling rules for the parsed next page element then operating with regard to the element according to the specified element-specific behavior, and otherwise if a page-specific behavior is specified for the fetched page resource then operating with regard to the element according to the specified page-specific behavior, and otherwise if a global crawl behavior is specified then operating with regard to the element according to the specified global crawl behavior, and otherwise operating with regard to the element according to a default crawl behavior; and repeating the processing until either all elements have been parsed and processed in accordance with the retrieved crawling rules, and wherein the default crawl behavior comprises extracting URLs of outbound links and adding the extracted URLs to the queue, storing text to a resource repository for further analysis; and repeating the steps of retrieving the next unprocessed URL through this repeating step until the queue is empty of unprocessed URLs; and wherein the retrieved crawling rules define the crawling behavior in terms of whether to record the resource text, whether to follow hyperlinks of the resource, whether to record text description in metadata associated with the page, whether to record keywords identified in the metadata associated with the page, whether to override a page title element, whether to exclude one or more identified resource pages, whether to exclude one or more identified domains. 18. The method of claim 12 , wherein the user-specified web crawl configuration further comprises user-specified throttling rules, the throttling rules comprising at least a plurality of a user-specified page pause time, a user-specified number of page crawler threads, and a user-specified maximum number of threads allocated per crawled domain; and wherein the default crawl behavior further comprises pausing at least the user-specified page pause time before fetching the next page resource, spawning up to the user-specified number of page crawler threads to perform the crawl, and for any given crawled domain, spawning up to the user-specified maximum number of threads allocated per crawled domain. | 0.751583 |
9,846,841 | 8 | 10 | 8. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: determining, by the data processing apparatus, a potential match candidate from among candidates ranked by predictors, each predictor respectively ranking the candidates according to likelihoods for matching an object as predicted by the respective predictor, and each predictor being different from each other predictor; identifying, for each predictor and by the data processing apparatus, a first value that specifies a likelihood of the potential match candidate for matching the object as predicted by the predictor; identifying, for each predictor and by the data processing apparatus, a second value that is proportional to the ranking of the potential match candidate as predicted by the predictor; determining, by the data processing apparatus, a class probability score for the potential match candidate using the first value for each predictor and the second value for each predictor, the class probability score representing a probability that the potential match candidate is a match to the object; determining, by the data processing apparatus, that the class probability score satisfies a threshold; and determining, by the data processing apparatus, that the potential match candidate matches the object in response to determining that the class probability score satisfies the threshold. | 8. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: determining, by the data processing apparatus, a potential match candidate from among candidates ranked by predictors, each predictor respectively ranking the candidates according to likelihoods for matching an object as predicted by the respective predictor, and each predictor being different from each other predictor; identifying, for each predictor and by the data processing apparatus, a first value that specifies a likelihood of the potential match candidate for matching the object as predicted by the predictor; identifying, for each predictor and by the data processing apparatus, a second value that is proportional to the ranking of the potential match candidate as predicted by the predictor; determining, by the data processing apparatus, a class probability score for the potential match candidate using the first value for each predictor and the second value for each predictor, the class probability score representing a probability that the potential match candidate is a match to the object; determining, by the data processing apparatus, that the class probability score satisfies a threshold; and determining, by the data processing apparatus, that the potential match candidate matches the object in response to determining that the class probability score satisfies the threshold. 10. The system of claim 8 , wherein the instructions upon execution cause the data processing apparatus to perform further operations comprising: identifying, for each predictor, a most likely candidate based on the ranking of the candidates as predicted by the predictor; determining a number of votes for each most likely candidate, the number of votes for a particular most likely candidate specifying the number of predictors for which the particular most likely candidate was identified as the most likely candidate for the predictor; and selecting the potential match candidate as the most likely candidate that has the most number of votes. | 0.586317 |
8,341,178 | 16 | 18 | 16. The computer-implemented method of claim 1 , further comprising: generating a report that includes the information that indicates a result of the comparison. | 16. The computer-implemented method of claim 1 , further comprising: generating a report that includes the information that indicates a result of the comparison. 18. The computer-implemented method of claim 16 , wherein: the report further includes a recommendation for a database query language statement in the set of targeted database query language statements whose performance in the second database system is worse than performance in the first database system; the recommendation is to create a plan baseline for the database query language statement; the plan baseline is the execution plan for the database query language statement in the first database system; and creation of the plan baseline for the database query language statement results in the plan baseline being used in executing the database query language statement in the second database system. | 0.5 |
9,619,642 | 1 | 4 | 1. A method for generating, by a processor, an image for use in a test to tell computers and humans apart comprising: receiving, by the processor, a selection of a range of characters corresponding to code points from Unicode plane 0, the selected range of characters at least including the 8-bit ASCII character range; receiving, by the processor, a selection of a font for the selected range of characters; testing, by the processor, each character in the selected range of characters, characters of the selected range of characters that pass the testing forming a challenge character subset, the testing comprising: determining if the character has a glyph in the selected font; determining if the character is a whitespace character; determining if the character leaves a visible impression; receiving, by the processor, a selection of a number of challenge characters; generating, in response to receiving a request for an image, by the processor: a challenge comprising a plurality of selected characters from the challenge character subset, the number of characters in the challenge equaling the selected number of challenge characters, and a response comprising a plurality of characters from the challenge character subset, the response having a character count that is greater than the selected number of challenge characters and the response including the characters in the challenge, each character in the response having a font size selected from a range having a predetermined maximum, the generated image comprising the generated challenge and the generated response; and calculating, by the processor, a solution threshold, the solution threshold being a value based on the selected font size of each of the characters in the challenge included in the response and a predetermined distance from the locations of each of the characters in the challenge included in the response. | 1. A method for generating, by a processor, an image for use in a test to tell computers and humans apart comprising: receiving, by the processor, a selection of a range of characters corresponding to code points from Unicode plane 0, the selected range of characters at least including the 8-bit ASCII character range; receiving, by the processor, a selection of a font for the selected range of characters; testing, by the processor, each character in the selected range of characters, characters of the selected range of characters that pass the testing forming a challenge character subset, the testing comprising: determining if the character has a glyph in the selected font; determining if the character is a whitespace character; determining if the character leaves a visible impression; receiving, by the processor, a selection of a number of challenge characters; generating, in response to receiving a request for an image, by the processor: a challenge comprising a plurality of selected characters from the challenge character subset, the number of characters in the challenge equaling the selected number of challenge characters, and a response comprising a plurality of characters from the challenge character subset, the response having a character count that is greater than the selected number of challenge characters and the response including the characters in the challenge, each character in the response having a font size selected from a range having a predetermined maximum, the generated image comprising the generated challenge and the generated response; and calculating, by the processor, a solution threshold, the solution threshold being a value based on the selected font size of each of the characters in the challenge included in the response and a predetermined distance from the locations of each of the characters in the challenge included in the response. 4. The method of claim 1 , wherein the selected range of characters further includes characters from Unicode points 0-4095. | 0.914106 |
9,367,525 | 8 | 9 | 8. The data processing apparatus of claim 1 , wherein the particular operators are identified by at least one of font type, font size, position and type of content, wherein the at least one of font type and font size are same across two or more of the page data. | 8. The data processing apparatus of claim 1 , wherein the particular operators are identified by at least one of font type, font size, position and type of content, wherein the at least one of font type and font size are same across two or more of the page data. 9. The data processing apparatus of claim 8 , wherein the particular operators are identified by font type and position and comprise number content, and wherein the page order determiner receives the particular operators, and the page order determiner orders the page data based on sequence of the number content associated with respective page data. | 0.5 |
9,177,057 | 11 | 17 | 11. One or more computer-readable media not a signal per se storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method comprising: receiving a search query; identifying a query context for the search query; analyzing the query context to identify one or more dominant concepts; identifying a location of each of the one or more dominant concepts within a concept graph; identifying a plurality of additional concepts having a relationship with the one or more dominant concepts within the concept graph; assigning a first weight to each additional concept representing a strength of relationship of each additional concept to the one or more dominant concepts within the concept graph; selecting a subset of the additional concepts based on the assigned weights to provide a set of expanded concepts; receiving a plurality of search results for the search query; analyzing each search result to determine whether each search result includes one or more of the expanded concepts; assigning one or more second weights to each search result representing a strength of relationship of each search result to the expanded concepts; varying a prominence of the search results such that one or more higher ranked search results are included in a listing on a search results page and one or more lower ranked search results are represented by one or more tabs on the search results page based on a combination of the first weights and second weights; and providing the one or more tabs for presentation in the search results page with the listing of the one or more higher ranked search results in the search results page. | 11. One or more computer-readable media not a signal per se storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method comprising: receiving a search query; identifying a query context for the search query; analyzing the query context to identify one or more dominant concepts; identifying a location of each of the one or more dominant concepts within a concept graph; identifying a plurality of additional concepts having a relationship with the one or more dominant concepts within the concept graph; assigning a first weight to each additional concept representing a strength of relationship of each additional concept to the one or more dominant concepts within the concept graph; selecting a subset of the additional concepts based on the assigned weights to provide a set of expanded concepts; receiving a plurality of search results for the search query; analyzing each search result to determine whether each search result includes one or more of the expanded concepts; assigning one or more second weights to each search result representing a strength of relationship of each search result to the expanded concepts; varying a prominence of the search results such that one or more higher ranked search results are included in a listing on a search results page and one or more lower ranked search results are represented by one or more tabs on the search results page based on a combination of the first weights and second weights; and providing the one or more tabs for presentation in the search results page with the listing of the one or more higher ranked search results in the search results page. 17. The one or more computer-readable media of claim 11 , wherein the plurality of search results are provided in conjunction with the search query. | 0.757377 |
7,533,362 | 12 | 15 | 12. A computer system, comprising: an input interface operable to parse a high-level language program, the high-level language program configured to run on a conventional central processing unit, wherein the input interface is operable to identify a hardware resource count included in the high-level language program, wherein the hardware resource count is associated with a code sequence in the high-level language program; a processor operable to generate hardware acceleration logic for implementing the code sequence using the hardware resource count, wherein the hardware resource count specifies the number of resources to use to implement the code sequence on a programmable chip. | 12. A computer system, comprising: an input interface operable to parse a high-level language program, the high-level language program configured to run on a conventional central processing unit, wherein the input interface is operable to identify a hardware resource count included in the high-level language program, wherein the hardware resource count is associated with a code sequence in the high-level language program; a processor operable to generate hardware acceleration logic for implementing the code sequence using the hardware resource count, wherein the hardware resource count specifies the number of resources to use to implement the code sequence on a programmable chip. 15. The computer system of claim 12 , wherein the hardware resource count specifies the number of logic elements used to implement the code sequence. | 0.534375 |
8,566,509 | 7 | 8 | 7. The method of claim 1 , further comprising processing, by said VMI FSM, a packet header token using an input/output (I/O) protocol on an adapter specified by an InfiniBand architecture, wherein said processing said packet header token includes: a port receiving a data packet that includes a payload and a packet header; storing said payload in a payload buffer; inserting said packet header in a second field of said packet header token, wherein said packet header token is said first input token, and wherein said second field of said packet header token is said second field of said first input token; extracting a queue pair (QP) number from said packet header, wherein said QP number identifies a QP that specifies a network connection in said InfiniBand architecture; storing said QP number in a first field of said packet header token, wherein said first field of said packet header token is said first field of said first input token, wherein said receiving said first input token includes receiving said packet header token from said port and at said VMI FSM. | 7. The method of claim 1 , further comprising processing, by said VMI FSM, a packet header token using an input/output (I/O) protocol on an adapter specified by an InfiniBand architecture, wherein said processing said packet header token includes: a port receiving a data packet that includes a payload and a packet header; storing said payload in a payload buffer; inserting said packet header in a second field of said packet header token, wherein said packet header token is said first input token, and wherein said second field of said packet header token is said second field of said first input token; extracting a queue pair (QP) number from said packet header, wherein said QP number identifies a QP that specifies a network connection in said InfiniBand architecture; storing said QP number in a first field of said packet header token, wherein said first field of said packet header token is said first field of said first input token, wherein said receiving said first input token includes receiving said packet header token from said port and at said VMI FSM. 8. The method of claim 7 , further comprising: determining a transport mode of said network connection specified by said QP is a reliable connect transport mode (RC) or a reliable datagram transport mode (RD); determining a packet sequence number (PSN) included in said packet header token is equal to an expected PSN (ePSN) included in said fetched context; and in response to said determining said transport mode of said QP is said RC or said RD and in response to said determining said PSN is equal to said ePSN, sending an acknowledgment to said port. | 0.5 |
8,560,529 | 1 | 5 | 1. A computer implemented method for comparing the distinctiveness of a plurality of sets within a collection of information, the method comprising: sampling, by a computer system, from the collection of information to generate at least one set; establishing, automatically, at least one identifying characteristic within the at least one set; determining a statistical distribution of the at least one identifying characteristic associated with the at least one set; and generating, by the computer system, a relative measurement of distinctiveness based on the statistical distribution of the at least one identifying characteristic associated with the at least one set and at least one other set, wherein the generating the relative measure of distinctiveness comprises accounting for a set size of a measured set based on a measurement of distinctiveness for a comparison set and a size for the comparison set, and normalizing the relative measurement of distinctiveness based on the set size of the measured set and the size for the comparison set. | 1. A computer implemented method for comparing the distinctiveness of a plurality of sets within a collection of information, the method comprising: sampling, by a computer system, from the collection of information to generate at least one set; establishing, automatically, at least one identifying characteristic within the at least one set; determining a statistical distribution of the at least one identifying characteristic associated with the at least one set; and generating, by the computer system, a relative measurement of distinctiveness based on the statistical distribution of the at least one identifying characteristic associated with the at least one set and at least one other set, wherein the generating the relative measure of distinctiveness comprises accounting for a set size of a measured set based on a measurement of distinctiveness for a comparison set and a size for the comparison set, and normalizing the relative measurement of distinctiveness based on the set size of the measured set and the size for the comparison set. 5. The method according to claim 1 , wherein the sampling to generate the at least one set further comprises generating the at least one set having a size based on a size of the at least one other set. | 0.772624 |
8,862,455 | 18 | 19 | 18. A computer system comprising the following: one or more processors; system memory; one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors, causes the computing system to perform a method for generating pluralization rules for multiple different languages, the method comprising the following: an act of accessing a resource identifier (ID) representing a user interface (UI) text string to determine a numerical amount for which a proper pluralization form is to be identified; an act of generating one or more string resource IDs for the corresponding UI text string, wherein the string resource IDs include different pluralization forms to be used with specified numerical amounts in multiple different languages, at least one of the generated string resource IDs including a language-specific pluralization form that applies to a plurality of languages including the indicated language and at least one other language; an act of passing one or more of the generated string resource IDs to a translator for translation into a specified language, wherein each generated string resource ID includes information indicating the one or more numerical amounts it is to be used with and the language it is to be used with; an act of receiving from the translator the properly translated string resource ID; and an act of displaying the text string corresponding to the translated string resource ID in the UI. | 18. A computer system comprising the following: one or more processors; system memory; one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors, causes the computing system to perform a method for generating pluralization rules for multiple different languages, the method comprising the following: an act of accessing a resource identifier (ID) representing a user interface (UI) text string to determine a numerical amount for which a proper pluralization form is to be identified; an act of generating one or more string resource IDs for the corresponding UI text string, wherein the string resource IDs include different pluralization forms to be used with specified numerical amounts in multiple different languages, at least one of the generated string resource IDs including a language-specific pluralization form that applies to a plurality of languages including the indicated language and at least one other language; an act of passing one or more of the generated string resource IDs to a translator for translation into a specified language, wherein each generated string resource ID includes information indicating the one or more numerical amounts it is to be used with and the language it is to be used with; an act of receiving from the translator the properly translated string resource ID; and an act of displaying the text string corresponding to the translated string resource ID in the UI. 19. The system of claim 18 , wherein translators for a given language are limited to using the generated resource IDs for translation. | 0.671569 |
8,219,599 | 10 | 11 | 10. A computer-implemented method for providing access to a knowledge base, comprising: converting a natural language question to an internal query that represents an interpretation of the natural language question and has an internal format compatible with structured data of the knowledge base, the structured data representing first knowledge; computing one or more responses to the natural language question by processing the internal query with reference to the structured data, wherein the one or more responses include second knowledge derived from the first knowledge in response to the internal query, the second knowledge not being stored in the knowledge base prior to receipt of the natural language question; and generating a definitive natural language answer corresponding to at least one of the one or more responses. | 10. A computer-implemented method for providing access to a knowledge base, comprising: converting a natural language question to an internal query that represents an interpretation of the natural language question and has an internal format compatible with structured data of the knowledge base, the structured data representing first knowledge; computing one or more responses to the natural language question by processing the internal query with reference to the structured data, wherein the one or more responses include second knowledge derived from the first knowledge in response to the internal query, the second knowledge not being stored in the knowledge base prior to receipt of the natural language question; and generating a definitive natural language answer corresponding to at least one of the one or more responses. 11. The method of claim 10 further comprising generating a detailed presentation for the definitive natural language answer that includes additional information relating to one or more objects represented in the natural language answer. | 0.522267 |
9,600,842 | 29 | 48 | 29. A computer program product embodied on at least one non-transitory computer readable medium and configured to cause at least one hardware processor to operate, the computer program product comprising: code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to identify at least one computer-readable Extensible Markup Language (XML)-compliant data document that is eXtensible Business Reporting Language (XBRL)-compliant and includes: a plurality of line items with a plurality of data values, and a plurality of computer-readable semantic tags that describe a semantic meaning of the data values, where the at least one computer-readable XML-compliant data document is capable of including multiple hierarchical relationships between two of the plurality of line items; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to parse the at least one computer-readable XML-compliant data document, by: receiving the at least one computer-readable XML-compliant data document, identifying the multiple hierarchical relationships between the two line items, and at least one of the computer-readable semantic tags that describes the semantic meaning of at least one of the data values included in the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to access a plurality of computer-readable rules including: a computer-readable datatype rule for validation of a type of data values, a computer-readable calculation rule for validation of a calculation involving data values, and a computer-readable unit rule for validation of a unit of data values; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to process the at least one computer-readable XML-compliant data document, by: identifying at least a subset of the computer-readable rules including at least one of: the computer-readable datatype rule for validation of the type of data values, the computer-readable calculation rule for validation of the calculation involving data values, or the computer-readable unit rule for validation of the unit of data values; and processing at least a portion of the data values of at least a portion of the plurality of line items of the at least one computer-readable XML-compliant data document, utilizing the at least subset of the computer-readable rules, and at least a portion of the computer-readable semantic tags of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to display a result of a validation of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to develop a report, by: identifying the at least one computer-readable semantic tag that describes the semantic meaning of the at least one data value included in the at least one computer-readable XML-compliant data document, and retrieving data from one or more sources to represent the at least one data value in the report. | 29. A computer program product embodied on at least one non-transitory computer readable medium and configured to cause at least one hardware processor to operate, the computer program product comprising: code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to identify at least one computer-readable Extensible Markup Language (XML)-compliant data document that is eXtensible Business Reporting Language (XBRL)-compliant and includes: a plurality of line items with a plurality of data values, and a plurality of computer-readable semantic tags that describe a semantic meaning of the data values, where the at least one computer-readable XML-compliant data document is capable of including multiple hierarchical relationships between two of the plurality of line items; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to parse the at least one computer-readable XML-compliant data document, by: receiving the at least one computer-readable XML-compliant data document, identifying the multiple hierarchical relationships between the two line items, and at least one of the computer-readable semantic tags that describes the semantic meaning of at least one of the data values included in the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to access a plurality of computer-readable rules including: a computer-readable datatype rule for validation of a type of data values, a computer-readable calculation rule for validation of a calculation involving data values, and a computer-readable unit rule for validation of a unit of data values; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to process the at least one computer-readable XML-compliant data document, by: identifying at least a subset of the computer-readable rules including at least one of: the computer-readable datatype rule for validation of the type of data values, the computer-readable calculation rule for validation of the calculation involving data values, or the computer-readable unit rule for validation of the unit of data values; and processing at least a portion of the data values of at least a portion of the plurality of line items of the at least one computer-readable XML-compliant data document, utilizing the at least subset of the computer-readable rules, and at least a portion of the computer-readable semantic tags of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to display a result of a validation of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to develop a report, by: identifying the at least one computer-readable semantic tag that describes the semantic meaning of the at least one data value included in the at least one computer-readable XML-compliant data document, and retrieving data from one or more sources to represent the at least one data value in the report. 48. The computer program product of claim 29 , wherein the computer program product is configured such that at least one of the computer-readable semantic tags includes a computer-readable semantic tag name. | 0.941293 |
9,753,918 | 1 | 11 | 1. A method comprising: receiving from a user an utterance in a first language including a first term; by a speech translation system, translating the utterance from the first language into a second language; receiving an indication from the user to initiate a user customization process for customizing one or more modules of the speech translation system to the user; and under the user customization process: receiving an indication from the user to add the first term to one or more modules of the speech translation system; in response to the received indication from the user, determining word class information for the first term; adding, by the speech translation system, the first term, the determined word class information, and at least a portion of the translation of the utterance in the second language to a first machine translation module associated with the first language of the speech translation system; and adding the first term and the at least a portion of the translation of the utterance in the second language to a shared database for a community such that the customization performed by the user is available for use by other users of the community in translations by the speech translation system. | 1. A method comprising: receiving from a user an utterance in a first language including a first term; by a speech translation system, translating the utterance from the first language into a second language; receiving an indication from the user to initiate a user customization process for customizing one or more modules of the speech translation system to the user; and under the user customization process: receiving an indication from the user to add the first term to one or more modules of the speech translation system; in response to the received indication from the user, determining word class information for the first term; adding, by the speech translation system, the first term, the determined word class information, and at least a portion of the translation of the utterance in the second language to a first machine translation module associated with the first language of the speech translation system; and adding the first term and the at least a portion of the translation of the utterance in the second language to a shared database for a community such that the customization performed by the user is available for use by other users of the community in translations by the speech translation system. 11. The method of claim 1 , further comprising: in response to the received indication from the user, determining a pronunciation in the first language for the first term; and adding the pronunciation in the first language to the shared database. | 0.702899 |
8,392,281 | 1 | 4 | 1. A system for presenting items complementary to an item of interest to a user, the system comprising: a data store that stores business rules data that define complementary items based at least in part on prior sales performance of the complementary items; and a computing device in communication with the data store that is operative to: retrieve from the data store the business rules data; generate one or more combinations of items for selection by the user, each combination of items generated for selection by the user as a unit based on an item of interest selected by the user, each combination including the item of interest selected by the user and one or more items that are complementary to the item of interest, each of the one or more complementary items being automatically selected in accordance with the business rules data; and process the business rules data to determine at least one of: a combination order for displaying the one or more combinations, and a complementary item order for displaying the multiple complementary items in each of the one or more combinations cause each of the one or more combinations of items to be displayed to the user in accordance with the business rules data as a pre-selected unit for purchase, with an indication of a total price for the unit; and for each of the combinations of items, cause a purchase control to be displayed, the purchase control selectable by the user to initiate a purchase of the item of interest and the one or more complementary items that are pre-selected for purchase together as a unit. | 1. A system for presenting items complementary to an item of interest to a user, the system comprising: a data store that stores business rules data that define complementary items based at least in part on prior sales performance of the complementary items; and a computing device in communication with the data store that is operative to: retrieve from the data store the business rules data; generate one or more combinations of items for selection by the user, each combination of items generated for selection by the user as a unit based on an item of interest selected by the user, each combination including the item of interest selected by the user and one or more items that are complementary to the item of interest, each of the one or more complementary items being automatically selected in accordance with the business rules data; and process the business rules data to determine at least one of: a combination order for displaying the one or more combinations, and a complementary item order for displaying the multiple complementary items in each of the one or more combinations cause each of the one or more combinations of items to be displayed to the user in accordance with the business rules data as a pre-selected unit for purchase, with an indication of a total price for the unit; and for each of the combinations of items, cause a purchase control to be displayed, the purchase control selectable by the user to initiate a purchase of the item of interest and the one or more complementary items that are pre-selected for purchase together as a unit. 4. The system of claim 1 , wherein the business rules data define complementary items based on the specification requirements of the item of interest. | 0.5 |
9,547,645 | 1 | 7 | 1. A machine translation apparatus comprising: a memory and; at least one processor coupled to the memory, the at least one processor configured to: obtain a first translated sentence generated by translating a first input sentence and a second translated sentence generated by translating a second input sentence, the second input sentence being a sentence into which the first input sentence is rewritten; acquire a difference between the first translated sentence and the second translated sentence; specify a first word in the first translated sentence corresponding to the difference, a second word in the second translated sentence corresponding to the difference and a related word that has a predetermined relationship with the first word and the second word, the related word being included in both of the first translated sentence and the second translated sentence; acquire a first appearance frequency and a second appearance frequency, the first appearance frequency indicating an appearance frequency of a combination of the first word and the related word with the predetermined relationship in a plurality of example sentences, the second appearance frequency indicating an appearance frequency of a combination of the second word and the related word with the predetermined relationship in the plurality of example sentences; generate, when the second appearance frequency is larger by a predetermined value than the first appearance frequency, a translation rule for replacing the first word with the second word; translate an input sentence entered by a user based on the generated translation rule; and output the translated input sentence. | 1. A machine translation apparatus comprising: a memory and; at least one processor coupled to the memory, the at least one processor configured to: obtain a first translated sentence generated by translating a first input sentence and a second translated sentence generated by translating a second input sentence, the second input sentence being a sentence into which the first input sentence is rewritten; acquire a difference between the first translated sentence and the second translated sentence; specify a first word in the first translated sentence corresponding to the difference, a second word in the second translated sentence corresponding to the difference and a related word that has a predetermined relationship with the first word and the second word, the related word being included in both of the first translated sentence and the second translated sentence; acquire a first appearance frequency and a second appearance frequency, the first appearance frequency indicating an appearance frequency of a combination of the first word and the related word with the predetermined relationship in a plurality of example sentences, the second appearance frequency indicating an appearance frequency of a combination of the second word and the related word with the predetermined relationship in the plurality of example sentences; generate, when the second appearance frequency is larger by a predetermined value than the first appearance frequency, a translation rule for replacing the first word with the second word; translate an input sentence entered by a user based on the generated translation rule; and output the translated input sentence. 7. The machine translation apparatus according to claim 1 , wherein the second input sentence being a sentence into which the first input sentence is rewritten so that the second translated sentence is a more accurate translation than the first translated sentence. | 0.553872 |
9,653,076 | 1 | 10 | 1. A display device for converting voice data to a text the display device comprising: a storage unit configured to store the voice data; a display unit configured to display the text; a sensor unit configured to detect a touch input to the display unit; and a processor configured to: convert the voice data to the text, display the converted text in the display unit, display a text preview interface in response to a first touch input, wherein the text preview interface previews at least a part of the text converted from the voice data in the display unit, detect a second touch input, wherein the second touch input corresponds to drag touch input including a length, determine an amount of the text displayed in a text output interface based on a predetermined output font size and the length of the second touch input, display the text in the text output interface in response to the second touch input, wherein the text output interface displays the text which is a part of displayed the text preview interface in the display unit, and provide different graphic effects to the text preview interface from the text output interface when the text output interface is displayed. | 1. A display device for converting voice data to a text the display device comprising: a storage unit configured to store the voice data; a display unit configured to display the text; a sensor unit configured to detect a touch input to the display unit; and a processor configured to: convert the voice data to the text, display the converted text in the display unit, display a text preview interface in response to a first touch input, wherein the text preview interface previews at least a part of the text converted from the voice data in the display unit, detect a second touch input, wherein the second touch input corresponds to drag touch input including a length, determine an amount of the text displayed in a text output interface based on a predetermined output font size and the length of the second touch input, display the text in the text output interface in response to the second touch input, wherein the text output interface displays the text which is a part of displayed the text preview interface in the display unit, and provide different graphic effects to the text preview interface from the text output interface when the text output interface is displayed. 10. The display device according to claim 1 , wherein the processor further deletes the text displayed in the text preview interface in response to a third touch input, and an amount of the text which is deleted is determined on the basis of a predetermined preview font size and a length of the third touch input. | 0.557746 |
9,501,551 | 2 | 3 | 2. The system of claim 1 , wherein the categorization service is further operative to transmit the updated first item information to the network-based service. | 2. The system of claim 1 , wherein the categorization service is further operative to transmit the updated first item information to the network-based service. 3. The system of claim 2 , wherein the network-based service is further operative to store the updated first item information in the data store. | 0.5 |
9,036,950 | 5 | 10 | 5. The system of claim 1 , wherein the processing electronics are further configured to predict the second textual passage that will be read by the user based on an amount of text between the first textual passage and the second textual passage. | 5. The system of claim 1 , wherein the processing electronics are further configured to predict the second textual passage that will be read by the user based on an amount of text between the first textual passage and the second textual passage. 10. The system of claim 5 , wherein the amount of text between the first textual passage and the second textual passage comprises a number of letters. | 0.506579 |
8,965,820 | 6 | 8 | 6. A non-transitory computer readable storage medium embodying a computer program for performing a method, said method comprising: causing a classification engine to receive unclassified data comprising a first variable and a second variable of a purchase transaction; causing the classification engine to reference a first ruleset reflecting a statistical classification scheme to generate a first classification based upon the first variable, the second variable, and a rule of the first ruleset; and causing the classification engine to communicate the first classification to a user, wherein the first ruleset further comprises a filtered rule selected from at least one of, a rule generating classifications exceeding a threshold; a rule generating classifications with a lack a dominant classification choice; a rule generating a top outcome that is not classified; a rule generating a top outcome associated with less than a percentage of a total spend; a rule for which a dimension value is blank. | 6. A non-transitory computer readable storage medium embodying a computer program for performing a method, said method comprising: causing a classification engine to receive unclassified data comprising a first variable and a second variable of a purchase transaction; causing the classification engine to reference a first ruleset reflecting a statistical classification scheme to generate a first classification based upon the first variable, the second variable, and a rule of the first ruleset; and causing the classification engine to communicate the first classification to a user, wherein the first ruleset further comprises a filtered rule selected from at least one of, a rule generating classifications exceeding a threshold; a rule generating classifications with a lack a dominant classification choice; a rule generating a top outcome that is not classified; a rule generating a top outcome associated with less than a percentage of a total spend; a rule for which a dimension value is blank. 8. A non-transitory computer readable storage medium as in claim 6 wherein the first variable comprises buying location, source system, line of business, cost center, functional area, supplier capabilities, item description, account description, organization, or department. | 0.698901 |
8,694,500 | 1 | 2 | 1. A method of providing services in a network, the method comprising: storing structured service documents defining available services in a database in at least one network element; receiving a service request in the at least one network element from a service requestor, the service request comprising a structured request document, the structured request document containing a plurality of nodes; forming a Path and Parent Associated Node (PPAN) element for each node in the structured request document, each PPAN element being a data structure containing a path level of a current node in the structured request document, a name and value pair associated with the current element, and a name and value pair of a parent element of the current element, the PPAN element not containing additional information about structure of the structured request document other than the path level of the current node and the parent-child relationship of the current node and its parent node; using the PPAN elements from the structured request document to identify a subset of the stored structured service documents that contain data and structure that match the PPAN elements; and providing to the service requestor, at least part of an structured service document in the identified subset of structured service documents to enable the service requestor to access the service defined by the structured service document of which at least part was provided. | 1. A method of providing services in a network, the method comprising: storing structured service documents defining available services in a database in at least one network element; receiving a service request in the at least one network element from a service requestor, the service request comprising a structured request document, the structured request document containing a plurality of nodes; forming a Path and Parent Associated Node (PPAN) element for each node in the structured request document, each PPAN element being a data structure containing a path level of a current node in the structured request document, a name and value pair associated with the current element, and a name and value pair of a parent element of the current element, the PPAN element not containing additional information about structure of the structured request document other than the path level of the current node and the parent-child relationship of the current node and its parent node; using the PPAN elements from the structured request document to identify a subset of the stored structured service documents that contain data and structure that match the PPAN elements; and providing to the service requestor, at least part of an structured service document in the identified subset of structured service documents to enable the service requestor to access the service defined by the structured service document of which at least part was provided. 2. The method of claim 1 , comprising the service requestor accessing the service defined by the structured service document of which at least part was provided using information in the provided at least part of the structured service document. | 0.587838 |
8,713,003 | 20 | 21 | 20. The method of claim 17 further comprising determining if the relevance measure is above a predetermined value. | 20. The method of claim 17 further comprising determining if the relevance measure is above a predetermined value. 21. The method of claim 20 further comprising linking the at least one of the one or more documents, applications, sound or visual media to a semantic domain when the relevance measure is greater than the predetermined value. | 0.5 |
9,881,000 | 7 | 12 | 7. A system for mitigating sentiment model overfitting, the system comprising: a processor; and a memory communicably coupled to the processor, wherein the memory includes computer instructions configured to cause the processor to: determine, using a first sentiment model having a current list of keywords and respective weights, respective sentiment results for a plurality of posts; receive sentiment feedback for the respective sentiment results; display a first set of posts which are in the plurality of posts and have a sentiment feedback not matching the respective sentiment results; display: keywords which appear in the first set of posts; and the keywords' respective weights; receive a first change including at least one of: a first proposed change to a respective weight of one or more of the keywords; a first proposed deletion of one or more of the keywords; or a first proposed new keyword and a respective weight of the first proposed new keyword; maintain unchanged the current list of keywords and respective weights while creating a proposed list of keywords and respective weights by applying the first change to the current list of keywords and respective weights; analyze, using the proposed list of keywords and respective weights, the first set of posts; enable identifying overfitting by displaying sentiment results for the first set of posts produced using the proposed list of keywords and respective weights; receive a second change including at least one of: a second proposed change to a respective weight of one or more of the keywords; a second proposed deletion of one or more of the keywords; or a second proposed new keyword and a respective weight of the second proposed new keyword; update the proposed list of keywords and respective weights by applying the second change to the proposed list of keywords and respective weights; after applying the second change to the proposed list of keywords and respective weights, re-analyze the first set of posts using the proposed list of keywords and respective weights; enable the identification of overfitting by the display of sentiment results for the first set of posts produced using the proposed list of keywords and respective weights; and create a second sentiment model by replacing the current list of keywords and respective weights with the proposed list of keywords and respective weights. | 7. A system for mitigating sentiment model overfitting, the system comprising: a processor; and a memory communicably coupled to the processor, wherein the memory includes computer instructions configured to cause the processor to: determine, using a first sentiment model having a current list of keywords and respective weights, respective sentiment results for a plurality of posts; receive sentiment feedback for the respective sentiment results; display a first set of posts which are in the plurality of posts and have a sentiment feedback not matching the respective sentiment results; display: keywords which appear in the first set of posts; and the keywords' respective weights; receive a first change including at least one of: a first proposed change to a respective weight of one or more of the keywords; a first proposed deletion of one or more of the keywords; or a first proposed new keyword and a respective weight of the first proposed new keyword; maintain unchanged the current list of keywords and respective weights while creating a proposed list of keywords and respective weights by applying the first change to the current list of keywords and respective weights; analyze, using the proposed list of keywords and respective weights, the first set of posts; enable identifying overfitting by displaying sentiment results for the first set of posts produced using the proposed list of keywords and respective weights; receive a second change including at least one of: a second proposed change to a respective weight of one or more of the keywords; a second proposed deletion of one or more of the keywords; or a second proposed new keyword and a respective weight of the second proposed new keyword; update the proposed list of keywords and respective weights by applying the second change to the proposed list of keywords and respective weights; after applying the second change to the proposed list of keywords and respective weights, re-analyze the first set of posts using the proposed list of keywords and respective weights; enable the identification of overfitting by the display of sentiment results for the first set of posts produced using the proposed list of keywords and respective weights; and create a second sentiment model by replacing the current list of keywords and respective weights with the proposed list of keywords and respective weights. 12. The system of claim 7 , wherein the computer instructions further comprise computer instructions to cause the processor to: calculate, for the sentiment results produced using the proposed list of keywords and respective weights, precision for at least one of negative sentiment, neutral sentiment, and positive sentiment; and display the results of the calculating. | 0.796031 |
9,916,284 | 1 | 4 | 1. A computer program product for generating an appendix from document content comprising: a non-transitory computer readable storage medium, the document analytics system including program instructions executable by a processor, the program instructions comprising: program instructions to execute a zoning and structural analysis phase, wherein the zoning and structural analysis phase comprises program instructions to identify a document structure, and program instructions to store the identified document structure; in response to completing the zoning and structural analysis phase, program instructions to execute a semantic relationship extraction phase, wherein the semantic relationship extraction phase comprises program instructions to extract semantic relationships from the stored identified document structure, and program instructions to store the extracted semantic relationships, and wherein the semantic relationship extraction phase further comprises: program instructions to extract a semantic relationship from each stored identified sentence, wherein the semantic relationship comprises a subject, a predicate, and an object; responsive to extracting and identifying the semantic relationship, program instructions to apply statistical distribution analysis to record a position where the subject and the object appear in the document; program instructions to identify and eliminate a trivial relation, wherein the trivial relation does not relate to a main topic of the document and based on the trivial relation having at least one of: the subject being evenly distributed within a section of the document, wherein a section is selected from a group consisting of a sentence, a paragraph, a page, a chapter, and the document as a whole; and the object being evenly distributed within the section of the document; and program instructions to store a non-trivial relation in persistent storage; in response to completing the semantic relationship extraction phase, program instructions to execute an analytics and relevance determination phase wherein the analytics and relevance determination phase comprises program instructions to identify candidate appendix topics in the stored extracted semantic relationships based on a degree of interdependency between the semantic relationships and program instructions to store the identified candidate appendix topics; in response to completing the analytics and relevance determination phase, program instructions to execute a web mining phase wherein the web mining phase comprises program instructions to calculate a measure of relevance of the mined web page to the stored candidate appendix topics and eliminate non-relevant intermediate results; and based on the web mining phase returning results relevant to a topic of the document, program instructions to generate the appendix. | 1. A computer program product for generating an appendix from document content comprising: a non-transitory computer readable storage medium, the document analytics system including program instructions executable by a processor, the program instructions comprising: program instructions to execute a zoning and structural analysis phase, wherein the zoning and structural analysis phase comprises program instructions to identify a document structure, and program instructions to store the identified document structure; in response to completing the zoning and structural analysis phase, program instructions to execute a semantic relationship extraction phase, wherein the semantic relationship extraction phase comprises program instructions to extract semantic relationships from the stored identified document structure, and program instructions to store the extracted semantic relationships, and wherein the semantic relationship extraction phase further comprises: program instructions to extract a semantic relationship from each stored identified sentence, wherein the semantic relationship comprises a subject, a predicate, and an object; responsive to extracting and identifying the semantic relationship, program instructions to apply statistical distribution analysis to record a position where the subject and the object appear in the document; program instructions to identify and eliminate a trivial relation, wherein the trivial relation does not relate to a main topic of the document and based on the trivial relation having at least one of: the subject being evenly distributed within a section of the document, wherein a section is selected from a group consisting of a sentence, a paragraph, a page, a chapter, and the document as a whole; and the object being evenly distributed within the section of the document; and program instructions to store a non-trivial relation in persistent storage; in response to completing the semantic relationship extraction phase, program instructions to execute an analytics and relevance determination phase wherein the analytics and relevance determination phase comprises program instructions to identify candidate appendix topics in the stored extracted semantic relationships based on a degree of interdependency between the semantic relationships and program instructions to store the identified candidate appendix topics; in response to completing the analytics and relevance determination phase, program instructions to execute a web mining phase wherein the web mining phase comprises program instructions to calculate a measure of relevance of the mined web page to the stored candidate appendix topics and eliminate non-relevant intermediate results; and based on the web mining phase returning results relevant to a topic of the document, program instructions to generate the appendix. 4. The computer program product of claim 1 , wherein the analytics and relevance determination phase further comprises: program instructions to detect at least one interdependency between two or more non-trivial relations in the stored extracted semantic relationships; program instructions to graph the at least one interdependency between the two or more non-trivial relations, wherein the two or more non-trivial relations comprise nodes of a graph, and the at least one interdependency comprise an edge of the graph; and program instructions to identify candidate appendix topics, based on a degree of relatedness between the nodes of the graph, centrality, between-ness, and connected-ness; and program instructions to store the identified candidate appendix topics in persistent storage. | 0.5 |
8,048,115 | 1 | 9 | 1. A surgical tool for implanting a dynamic bone anchor having a deflectable post extending from a housing at a proximal end of the dynamic bone anchor, the surgical tool comprising: an elongate shaft having, at a distal end, a head adapted to engage the dynamic bone anchor; the head having a socket adapted to engage the housing of the dynamic bone anchor; the head further including a retainer adapted to engage the deflectable post to retain the deflectable post within the socket; the elongate shaft further having at the proximal end a handle for turning the shaft in order to turn the housing of the dynamic bone anchor to implant the dynamic bone anchor in a vertebra; and the elongate shaft further having adjacent the handle an actuator to cause the retainer to release the deflectable post after implantation of the bone anchor in the vertebra. | 1. A surgical tool for implanting a dynamic bone anchor having a deflectable post extending from a housing at a proximal end of the dynamic bone anchor, the surgical tool comprising: an elongate shaft having, at a distal end, a head adapted to engage the dynamic bone anchor; the head having a socket adapted to engage the housing of the dynamic bone anchor; the head further including a retainer adapted to engage the deflectable post to retain the deflectable post within the socket; the elongate shaft further having at the proximal end a handle for turning the shaft in order to turn the housing of the dynamic bone anchor to implant the dynamic bone anchor in a vertebra; and the elongate shaft further having adjacent the handle an actuator to cause the retainer to release the deflectable post after implantation of the bone anchor in the vertebra. 9. The surgical tool of claim 1 , wherein the socket has a plurality of internal surface features adapted to be complementary to external surface features of the housing of the dynamic bone anchor. | 0.678105 |
8,902,274 | 2 | 3 | 2. The method of claim 1 , further comprising: discovering followers from the meeting recording; generating a followers notification without the option to manipulate the meeting recording, and comprising access to a portion of meeting recording; and sending the followers notification to the followers. | 2. The method of claim 1 , further comprising: discovering followers from the meeting recording; generating a followers notification without the option to manipulate the meeting recording, and comprising access to a portion of meeting recording; and sending the followers notification to the followers. 3. The method of claim 2 , wherein the discovering the followers comprises: running automatic speech recognition and named entity extraction algorithms on the meeting recording; discovering spoken names in the meeting recording; and associating the followers with a portion of the spoken names not corresponding to attendees in the meeting recording. | 0.5 |
9,135,254 | 1 | 3 | 1. A computer-implemented method of searching documents within a collection comprising: partitioning, via a hardware processor, the collection into a plurality of document segments based on a range of values for a document attribute, wherein each document segment is associated with a different value range for the document attribute and includes documents each with a value for the document attribute within the associated value range; adjusting, via a hardware processor, a quantity of documents within one or more document segments to attain a predetermined range fir a segment characteristic for each of the document segments, wherein the segment characteristic includes a quantity of searches performed for each document segment; determining, via a hardware processor, one or more document segments to search based on one or more search criteria within a search request pertaining to the document attribute; and searching, via a hardware processor, the determined one or more document segments for information satisfying the search request. | 1. A computer-implemented method of searching documents within a collection comprising: partitioning, via a hardware processor, the collection into a plurality of document segments based on a range of values for a document attribute, wherein each document segment is associated with a different value range for the document attribute and includes documents each with a value for the document attribute within the associated value range; adjusting, via a hardware processor, a quantity of documents within one or more document segments to attain a predetermined range fir a segment characteristic for each of the document segments, wherein the segment characteristic includes a quantity of searches performed for each document segment; determining, via a hardware processor, one or more document segments to search based on one or more search criteria within a search request pertaining to the document attribute; and searching, via a hardware processor, the determined one or more document segments for information satisfying the search request. 3. The computer-implemented method of claim 1 , wherein partitioning the collection further includes: storing associations of document segments and value ranges for the document attribute within a database object. | 0.5 |
9,767,121 | 13 | 17 | 13. A non-transitory computer readable medium configured to store instructions executable by a computer processor, the instructions for: receiving a query from a user device operated by a user, the query comprising one or more query tokens; determining one or more candidate location tokens from the one or more query tokens; generating a relevance score for each of the one or more candidate location tokens; determining a target location based on the relevance scores, the candidate location tokens, and a geodata index; determining a query classification using the one or more query tokens and a domain index; selecting a plurality of query response candidates from a content index based on the query classification and the target location, each query response candidate comprising a document associated with a location, wherein the instructions for selecting a plurality of query response candidates from a content index based on the query classification and the target location, further comprise instructions for: determining a search radius distance based on the query classification, wherein the search radius distance is dependent on the query classification such that a query response is relevant for a particular search type, and wherein the search radius distance is preset based on a distance a user expects to travel to the target location; determining if a document in the content index is associated with a location that is within the search radius distance of the target location; and selecting the document based at least in part on the determination that it is associated with a location that is within the search radius distance of the target location; generating a relevance score for each of the plurality of query response candidates; selecting a query response from the plurality of query response candidates based on their relevance scores; and sending the selected query response to the user device. | 13. A non-transitory computer readable medium configured to store instructions executable by a computer processor, the instructions for: receiving a query from a user device operated by a user, the query comprising one or more query tokens; determining one or more candidate location tokens from the one or more query tokens; generating a relevance score for each of the one or more candidate location tokens; determining a target location based on the relevance scores, the candidate location tokens, and a geodata index; determining a query classification using the one or more query tokens and a domain index; selecting a plurality of query response candidates from a content index based on the query classification and the target location, each query response candidate comprising a document associated with a location, wherein the instructions for selecting a plurality of query response candidates from a content index based on the query classification and the target location, further comprise instructions for: determining a search radius distance based on the query classification, wherein the search radius distance is dependent on the query classification such that a query response is relevant for a particular search type, and wherein the search radius distance is preset based on a distance a user expects to travel to the target location; determining if a document in the content index is associated with a location that is within the search radius distance of the target location; and selecting the document based at least in part on the determination that it is associated with a location that is within the search radius distance of the target location; generating a relevance score for each of the plurality of query response candidates; selecting a query response from the plurality of query response candidates based on their relevance scores; and sending the selected query response to the user device. 17. The computer readable medium of claim 13 , wherein the instructions for generating a relevance score for each of the plurality of query response candidates, further comprise instructions for: determining a distance between the location associated with a query response candidate and the target location; and generating a relevance score based on the distance. | 0.582759 |
7,774,388 | 2 | 3 | 2. The apparatus of claim 1 , wherein the person state is described according to a plurality of classes, the plurality of classes comprising a real person class and a fictitious person class. | 2. The apparatus of claim 1 , wherein the person state is described according to a plurality of classes, the plurality of classes comprising a real person class and a fictitious person class. 3. The apparatus of claim 2 , wherein the property state is described according to a second plurality of classes, the second plurality of classes comprising a real property class, a personal property class, an intellectual property class, and a public property class. | 0.5 |
7,680,767 | 11 | 12 | 11. A computer readable storage medium having stored thereon a plurality of computer executable instructions that are executable by a computer to implement a data access system for providing data services to an application, the computer executable instructions comprising: computer executable instructions for generating a query view that expresses at least a portion of an application schema associated with said application in terms of a database schema associated with a database; computer executable instructions for generating an update view that expresses at least a portion of said database schema in terms of said application schema; computer executable instructions for processing a query request from the application requesting access to data by utilizing said query view to query said database on behalf of said requesting application; and computer executable instructions for processing an update request from the application requesting an update to data by utilizing said update view to update said database on behalf of said requesting application. | 11. A computer readable storage medium having stored thereon a plurality of computer executable instructions that are executable by a computer to implement a data access system for providing data services to an application, the computer executable instructions comprising: computer executable instructions for generating a query view that expresses at least a portion of an application schema associated with said application in terms of a database schema associated with a database; computer executable instructions for generating an update view that expresses at least a portion of said database schema in terms of said application schema; computer executable instructions for processing a query request from the application requesting access to data by utilizing said query view to query said database on behalf of said requesting application; and computer executable instructions for processing an update request from the application requesting an update to data by utilizing said update view to update said database on behalf of said requesting application. 12. The computer readable storage medium of claim 11 , further comprising computer executable instructions for receiving, from said requesting application, an object in a programming language, said object in a programming language comprising data for use in updating said database. | 0.553968 |
9,020,932 | 10 | 11 | 10. The system of claim 9 , wherein the retrieved search history data comprises unique user search history data that is associated with identity indicia that is unique to the user, and generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having common same occupational identity indicia; and wherein the processing unit, when executing the program instructions stored on the computer-readable storage medium via the computer readable memory, classifies the text string search query into the constituent primary search terms by weighting classifications determined as a function of the unique user search history data more highly than classifications determined as a function of the generic occupational identity search data, and weighting classifications determined as a function of the generic occupational identity search data more highly than any classifications generated by application of universal search history popularities common to all user histories. | 10. The system of claim 9 , wherein the retrieved search history data comprises unique user search history data that is associated with identity indicia that is unique to the user, and generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having common same occupational identity indicia; and wherein the processing unit, when executing the program instructions stored on the computer-readable storage medium via the computer readable memory, classifies the text string search query into the constituent primary search terms by weighting classifications determined as a function of the unique user search history data more highly than classifications determined as a function of the generic occupational identity search data, and weighting classifications determined as a function of the generic occupational identity search data more highly than any classifications generated by application of universal search history popularities common to all user histories. 11. The system of claim 10 , wherein the processing unit, when executing the program instructions stored on the computer-readable storage medium via the computer readable memory, further identifies the generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having the common occupational identity indicia by: recognizing a type of network access used by the user to submit the text string query; determining a predominant occupational identity associated with the recognized type of network access; and retrieving search history common to pluralities of users that share the determined predominant occupational identity as the generic occupational identity search data. | 0.5 |
8,510,294 | 15 | 20 | 15. A system comprising: at least one processor; and a computer readable medium containing program code that when executed causes the at least one processor to perform operations comprising: (a) receiving a search query; (b) determining a first population associated with the search query based on at least one sender of the search query; (c) determining a first article associated with the search query; and (d) determining a first ranking score for the first article based at least in part on data associated with the first population. | 15. A system comprising: at least one processor; and a computer readable medium containing program code that when executed causes the at least one processor to perform operations comprising: (a) receiving a search query; (b) determining a first population associated with the search query based on at least one sender of the search query; (c) determining a first article associated with the search query; and (d) determining a first ranking score for the first article based at least in part on data associated with the first population. 20. The system of claim 15 , wherein the data associated with the first population comprises a selection score for the first article in a context of the first population. | 0.554974 |
5,559,928 | 12 | 13 | 12. The data processing system for performing the fuzzy inference operation of claim 11 wherein the decoder decodes the second plurality of rule codes to generate a second plurality of decoded signals. | 12. The data processing system for performing the fuzzy inference operation of claim 11 wherein the decoder decodes the second plurality of rule codes to generate a second plurality of decoded signals. 13. The data processing system for performing the fuzzy inference operation of claim 12 wherein the rule bits generating circuit further comprises: second logic means coupled to the decoder for receiving the second plurality of decoded signals, the second logic means logically combining the first plurality of decoded signals and the second plurality of decoded signals to generate a second plurality of rule signals. | 0.5 |
9,286,451 | 9 | 10 | 9. The apparatus according to claim 8 , wherein the first virtual keyboard generating unit comprises at least one of: a key-character associations generating unit configured to randomly generate associations between keys on the first virtual keyboard and characters; and a layout generating unit configured to randomly generate a key layout of the first virtual keyboard. | 9. The apparatus according to claim 8 , wherein the first virtual keyboard generating unit comprises at least one of: a key-character associations generating unit configured to randomly generate associations between keys on the first virtual keyboard and characters; and a layout generating unit configured to randomly generate a key layout of the first virtual keyboard. 10. The apparatus according to claim 9 , wherein the key-character associations generating unit comprises at least one of: a unit configured to randomly assign characters to keys on the first virtual keyboard; and a unit configured to randomly determine the number of characters associated with a key on the first virtual keyboard. | 0.508902 |
7,680,812 | 34 | 35 | 34. The method of claim 33 , further comprising: rearranging said second hit list into a second ranked list. | 34. The method of claim 33 , further comprising: rearranging said second hit list into a second ranked list. 35. The method of claim 34 , further comprising: truncating said second ranked list. | 0.5 |
7,523,036 | 24 | 29 | 24. A text-to-speech synthesis apparatus comprising: a memory for storing phoneme data of a plurality of speaker voices; a selecting section for selecting any one of said plurality of speaker voices; a search section for searching said memory for the phoneme data of the speaker voices selected by said selecting section; a text-to-speech synthesis processing section for linking said phoneme data of said speaker voices retrieved by said search section to convert script data into a synthetic speech; a storage section for accumulating said synthetic speech converted from said script data on the basis of the phoneme data of said plurality of speaker voices; and a reproducing section for retrieving said synthetic speech of said speaker voices selected by said selecting section and reproducing said synthetic speech, wherein said text-to-speech synthesis processing means can convert said script into a synthetic speech including at least said two speaker voices including said speaker voice corresponding to said speaker voice identification data. | 24. A text-to-speech synthesis apparatus comprising: a memory for storing phoneme data of a plurality of speaker voices; a selecting section for selecting any one of said plurality of speaker voices; a search section for searching said memory for the phoneme data of the speaker voices selected by said selecting section; a text-to-speech synthesis processing section for linking said phoneme data of said speaker voices retrieved by said search section to convert script data into a synthetic speech; a storage section for accumulating said synthetic speech converted from said script data on the basis of the phoneme data of said plurality of speaker voices; and a reproducing section for retrieving said synthetic speech of said speaker voices selected by said selecting section and reproducing said synthetic speech, wherein said text-to-speech synthesis processing means can convert said script into a synthetic speech including at least said two speaker voices including said speaker voice corresponding to said speaker voice identification data. 29. The text-to-speech synthesis apparatus according to claim 24 , wherein said memory stores prosody data for each of said plurality of speaker voices, said search section searches for said prosody data along with said phoneme data of said one speaker selected by said selecting section; and said text-to-speech synthesis processing section converts said script data into a synthetic speech on the basis of said user-specified phoneme data and prosody data. | 0.5 |
8,874,605 | 12 | 15 | 12. A computer-readable non-transitory storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising: receiving a request from a user for one or more recommendations; determining a location distribution from historical location information associated with the user, wherein the location distribution indicates one or more probability distributions for one or more locations; determining a time distribution from historical context information associated with the user, wherein the time distribution indicates one or more probability distributions for one or more contexts, wherein a respective context includes contextual variables corresponding to at least one of: a location; a time; a weather condition; and a venue type; determining a joint distribution of two or more of the contextual variables that are based on the location distribution and the time distribution, wherein the joint distribution comprises statistical attributes that characterize dependent relationships between the two or more of the contextual variables, the statistical attributes including one or more of: a mean value; a median value; a mode; a maximum value; and a minimum value of the contextual variables; determining a hypothetical context based on the statistical attributes of the joint distribution and a current context, wherein the hypothetical context indicates one or more user preferences that are outside of the user's current context and explicit historical contexts; producing one or more recommendations for the user based on the hypothetical context; constructing a mapping function that maps a user context to a hypothetical context, wherein constructing the mapping function involves using one or more of: historical contexts associated with the request; prior hypothetical contexts; and the user's interactions associated with the user's past requests for a recommendation; and providing the one or more recommendations to the user. | 12. A computer-readable non-transitory storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising: receiving a request from a user for one or more recommendations; determining a location distribution from historical location information associated with the user, wherein the location distribution indicates one or more probability distributions for one or more locations; determining a time distribution from historical context information associated with the user, wherein the time distribution indicates one or more probability distributions for one or more contexts, wherein a respective context includes contextual variables corresponding to at least one of: a location; a time; a weather condition; and a venue type; determining a joint distribution of two or more of the contextual variables that are based on the location distribution and the time distribution, wherein the joint distribution comprises statistical attributes that characterize dependent relationships between the two or more of the contextual variables, the statistical attributes including one or more of: a mean value; a median value; a mode; a maximum value; and a minimum value of the contextual variables; determining a hypothetical context based on the statistical attributes of the joint distribution and a current context, wherein the hypothetical context indicates one or more user preferences that are outside of the user's current context and explicit historical contexts; producing one or more recommendations for the user based on the hypothetical context; constructing a mapping function that maps a user context to a hypothetical context, wherein constructing the mapping function involves using one or more of: historical contexts associated with the request; prior hypothetical contexts; and the user's interactions associated with the user's past requests for a recommendation; and providing the one or more recommendations to the user. 15. The computer-readable non-transitory storage medium of claim 12 , wherein determining a respective hypothetical context comprises one or more of: determining a weather-condition distribution for the location distribution and the time distribution; determining a distribution over context-related preferences; and determining a distribution over conditions related to the hypothetical context that may be inferred from publicly-available data about the distribution over other contextual variables. | 0.730355 |
9,658,771 | 1 | 2 | 1. A computer implemented system for enabling a user to input alphabets in an Indian language, said system comprising a user interface on a display and an analyzer, said user interface comprising: at least one display enabled keypad layout, said keypad layout comprising a plurality of keypad layers, each of said keypad layers incorporating the alphabets of the Indian language as selectable keys, said alphabets generated based on a script-grammar corresponding to the Indian language, said plurality of keypad layers comprising: a default keypad layer comprising a plurality of alphabets represented as selectable vowels and consonants; a first keypad layer comprising the vowels and consonants, and a plurality of modifiers; a second keypad layer comprising a plurality of matras, a plurality of halants, the vowels, the consonants, wherein said matras are formed by selectively combining the vowels and the consonants; and a third keypad layer comprising the plurality of matras and the plurality of modifiers; said plurality of keypad layers are incorporated onto the display enabled keypad layout and selectively displayed, based on selection of a key on at least one of said keypad layers; said analyzer cooperating with said user interface: triggers a display of the first keypad layer subsequent to the selection of a vowel on the default keypad layer, and triggers a display of the second keypad layer, in an event that a consonant has been selected from the default keypad layer; retriggers the display of the default keypad layer in an event that a modifier has been selected from the first keypad layer, and triggers a display of the third keypad layer in an event that a consonant has been selected from the first keypad layer, and generates a trigger to retain the display of the first keypad layer, in an event that a vowel has been selected from the first keypad layer; retriggers the display of the default keypad layer subsequent to selection of a halant from said second key pad layer, and retriggers the display of the first keypad layer, in an event that a matra has been selected from said second keypad layer: and retriggers the display of the default keypad layer, subsequent to selection of a modifier from the third keypad layer, and retriggers the display of the default keypad layer, subsequent to selection of a matra from the third keypad layer. | 1. A computer implemented system for enabling a user to input alphabets in an Indian language, said system comprising a user interface on a display and an analyzer, said user interface comprising: at least one display enabled keypad layout, said keypad layout comprising a plurality of keypad layers, each of said keypad layers incorporating the alphabets of the Indian language as selectable keys, said alphabets generated based on a script-grammar corresponding to the Indian language, said plurality of keypad layers comprising: a default keypad layer comprising a plurality of alphabets represented as selectable vowels and consonants; a first keypad layer comprising the vowels and consonants, and a plurality of modifiers; a second keypad layer comprising a plurality of matras, a plurality of halants, the vowels, the consonants, wherein said matras are formed by selectively combining the vowels and the consonants; and a third keypad layer comprising the plurality of matras and the plurality of modifiers; said plurality of keypad layers are incorporated onto the display enabled keypad layout and selectively displayed, based on selection of a key on at least one of said keypad layers; said analyzer cooperating with said user interface: triggers a display of the first keypad layer subsequent to the selection of a vowel on the default keypad layer, and triggers a display of the second keypad layer, in an event that a consonant has been selected from the default keypad layer; retriggers the display of the default keypad layer in an event that a modifier has been selected from the first keypad layer, and triggers a display of the third keypad layer in an event that a consonant has been selected from the first keypad layer, and generates a trigger to retain the display of the first keypad layer, in an event that a vowel has been selected from the first keypad layer; retriggers the display of the default keypad layer subsequent to selection of a halant from said second key pad layer, and retriggers the display of the first keypad layer, in an event that a matra has been selected from said second keypad layer: and retriggers the display of the default keypad layer, subsequent to selection of a modifier from the third keypad layer, and retriggers the display of the default keypad layer, subsequent to selection of a matra from the third keypad layer. 2. The display enabled keypad layout as claimed in claim 1 , wherein the default keypad layer further comprises a default base layer and a default toggle layer, wherein said default base layer comprises un-aspirated consonants, and wherein said default toggle layer comprises aspirated consonants. | 0.802264 |
8,214,351 | 18 | 19 | 18. The computer readable medium of claim 13 , wherein determining one or more rule engines that include the required functions comprises evaluating metadata describing properties of the plurality of rule engines. | 18. The computer readable medium of claim 13 , wherein determining one or more rule engines that include the required functions comprises evaluating metadata describing properties of the plurality of rule engines. 19. The computer readable medium of claim 18 , wherein selecting a rule engine to process the abstract rule further comprises: excluding, from the one or more rule engines determined to include the required functions, any rule engine having an expected performance that is below a pre-determined minimum. | 0.5 |
9,842,096 | 8 | 12 | 8. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program comprises a natural language processing pipeline configured to execute on a data processing system to: receive an input document to be ingested into a corpus; divide the input document into a plurality of input passages; identify whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts, wherein identifying whether a given input passage is a nonsense passage comprises: annotating, by an annotator in the natural language processing pipeline, the given input passage within the plurality of input passages with linguistic features to form an annotated passage; counting, by metric counters component in the natural language processing pipeline, a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts; determining, by the metric counters component of the natural language processing pipeline, a value for a metric based on the set of feature counts; and comparing, by a comparator component of the natural language processing pipeline, the value for the metric to a predetermined model threshold; filter each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages; and add the filtered plurality of input passages into the corpus. | 8. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program comprises a natural language processing pipeline configured to execute on a data processing system to: receive an input document to be ingested into a corpus; divide the input document into a plurality of input passages; identify whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts, wherein identifying whether a given input passage is a nonsense passage comprises: annotating, by an annotator in the natural language processing pipeline, the given input passage within the plurality of input passages with linguistic features to form an annotated passage; counting, by metric counters component in the natural language processing pipeline, a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts; determining, by the metric counters component of the natural language processing pipeline, a value for a metric based on the set of feature counts; and comparing, by a comparator component of the natural language processing pipeline, the value for the metric to a predetermined model threshold; filter each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages; and add the filtered plurality of input passages into the corpus. 12. The computer program product of claim 8 , wherein the metric comprises a ratio of a number of instances of a first part-of-speech to a number of instances of a second part-of-speech in the input passage. | 0.783019 |
9,066,046 | 25 | 28 | 25. A system for filtering objectionable words comprising: a closed caption analyzer executable by at least one processor and configured to identify a specified text in a closed caption text stream based on a comparison of each word in the closed caption text stream to at least one filter list; a closed caption audiotizer executable by the at least one processor and configured to generate an audio equivalent of the specified text by converting the specified text to a phonetic representation associated with at least one energy value; and an audio stream analyzer executable by the at least one processor and configured to match a portion of an audio signal with the specified text by comparing the at least one energy value of the audio equivalent with an energy of a comparative form of the audio signal involving a total energy of a speech slice and energy of one or more frequency bands of the speech slice, the audio stream analyzer further configured to filter the portion of the audio signal. | 25. A system for filtering objectionable words comprising: a closed caption analyzer executable by at least one processor and configured to identify a specified text in a closed caption text stream based on a comparison of each word in the closed caption text stream to at least one filter list; a closed caption audiotizer executable by the at least one processor and configured to generate an audio equivalent of the specified text by converting the specified text to a phonetic representation associated with at least one energy value; and an audio stream analyzer executable by the at least one processor and configured to match a portion of an audio signal with the specified text by comparing the at least one energy value of the audio equivalent with an energy of a comparative form of the audio signal involving a total energy of a speech slice and energy of one or more frequency bands of the speech slice, the audio stream analyzer further configured to filter the portion of the audio signal. 28. The system of claim 25 , wherein the portion of the audio signal is filtered by issuing a command to attenuate at least one of a magnitude or an amplitude of the portion of the audio signal. | 0.572687 |
9,659,010 | 1 | 5 | 1. A method for generating a composite of images in multiple languages when a request is made to capture an image of a screen, the method comprising: receiving, by one or more processors, a request to capture a first graphical user interface (GUI) display of an application in a first language available to the application; iterating, by one or more processors, over GUI elements of the first GUI display to locate bundle keys from a first language bundle for a second language; and generating, by one or more processors, a second GUI display for the first language available to the application, wherein the second GUI display is a recreation of images within the first GUI display, and wherein generating the second GUI comprises: retrieving, by one or more processors, a bundle name and a first bundle key from the first language bundle for the second language and a second bundle key from a second language bundle for the first language; and running, by one or more processors, the application a second time, using the second bundle key from the second language bundle for the first language in place of the first bundle key from the first language bundle for the second language. | 1. A method for generating a composite of images in multiple languages when a request is made to capture an image of a screen, the method comprising: receiving, by one or more processors, a request to capture a first graphical user interface (GUI) display of an application in a first language available to the application; iterating, by one or more processors, over GUI elements of the first GUI display to locate bundle keys from a first language bundle for a second language; and generating, by one or more processors, a second GUI display for the first language available to the application, wherein the second GUI display is a recreation of images within the first GUI display, and wherein generating the second GUI comprises: retrieving, by one or more processors, a bundle name and a first bundle key from the first language bundle for the second language and a second bundle key from a second language bundle for the first language; and running, by one or more processors, the application a second time, using the second bundle key from the second language bundle for the first language in place of the first bundle key from the first language bundle for the second language. 5. The method of claim 1 , further comprising: capturing, by one or more processors, messages written to the first GUI, wherein the messages include key presses, mouse movements, action selections, and timers expiring. | 0.751142 |
9,141,853 | 5 | 7 | 5. The computer program product of claim 1 , wherein the program instructions are further configured to cause the computer system to train the extraction field template using a marked-up sample document by performing the operations of: using markup information in the marked-up sample document to locate an example prior block for the specific field type or an example post block for the specific field type; converting the example prior block to example prior block information or the example post block to example post block information, wherein example prior block information or example post block information includes token frequency information, token occurrence information, token weight information, and block weight information; and updating the token weight information for the example prior block or the example post block based on token frequency information and token occurrence information. | 5. The computer program product of claim 1 , wherein the program instructions are further configured to cause the computer system to train the extraction field template using a marked-up sample document by performing the operations of: using markup information in the marked-up sample document to locate an example prior block for the specific field type or an example post block for the specific field type; converting the example prior block to example prior block information or the example post block to example post block information, wherein example prior block information or example post block information includes token frequency information, token occurrence information, token weight information, and block weight information; and updating the token weight information for the example prior block or the example post block based on token frequency information and token occurrence information. 7. The computer program product of claim 5 , wherein training the extraction field template further comprises: updating the block weight information based on the token weight information. | 0.5 |
Subsets and Splits